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Xavier A, Campagna MP, Maltby VE, Kilpatrick T, Taylor BV, Butzkueven H, Ponsonby AL, Scott RJ, Jokubaitis VG, Lea RA, Lechner-Scott J. Interferon beta treatment is a potent and targeted epigenetic modifier in multiple sclerosis. Front Immunol 2023; 14:1162796. [PMID: 37325639 PMCID: PMC10266220 DOI: 10.3389/fimmu.2023.1162796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 05/12/2023] [Indexed: 06/17/2023] Open
Abstract
Introduction Multiple Sclerosis (MS) has a complex pathophysiology that involves genetic and environmental factors. DNA methylation (DNAm) is one epigenetic mechanism that can reversibly modulate gene expression. Cell specific DNAm changes have been associated with MS, and some MS therapies such as dimethyl fumarate can influence DNAm. Interferon Beta (IFNβ), was one of the first disease modifying therapies in multiple sclerosis (MS). However, how IFNβ reduces disease burden in MS is not fully understood and little is known about the precise effect of IFNβ treatment on methylation. Methods The objective of this study was to determine the changes in DNAm associated with INFβ use, using methylation arrays and statistical deconvolutions on two separate datasets (total ntreated = 64, nuntreated = 285). Results We show that IFNβ treatment in people with MS modifies the methylation profile of interferon response genes in a strong, targeted, and reproducible manner. Using these identified methylation differences, we constructed a methylation treatment score (MTS) that is an accurate discriminator between untreated and treated patients (Area under the curve = 0.83). This MTS is time-sensitive and in consistent with previously identified IFNβ treatment therapeutic lag. This suggests that methylation changes are required for treatment efficacy. Overrepresentation analysis found that IFNβ treatment recruits the endogenous anti-viral molecular machinery. Finally, statistical deconvolution revealed that dendritic cells and regulatory CD4+ T cells were most affected by IFNβ induced methylation changes. Discussion In conclusion, our study shows that IFNβ treatment is a potent and targeted epigenetic modifier in multiple sclerosis.
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Affiliation(s)
- Alexandre Xavier
- School of Biomedical Science and Pharmacy, University of Newcastle, Newcastle, NSW, Australia
| | - Maria Pia Campagna
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
| | - Vicki E. Maltby
- Hunter Medical Research Institute, Immune Health research program, Newcastle, NSW, Australia
- Department of Neurology, John Hunter Hospital, Newcastle, NSW, Australia
- School of Medicine and Public Health, University of Newcastle, Newcastle, NSW, Australia
| | - Trevor Kilpatrick
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
| | - Bruce V. Taylor
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, Australia
| | - Helmut Butzkueven
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
- Neuro-Immunology Registry, MSBase Foundation, Melbourne, VIC, Australia
| | - Anne-Louise Ponsonby
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
| | - Rodney J. Scott
- School of Biomedical Science and Pharmacy, University of Newcastle, Newcastle, NSW, Australia
- New South Wales (NSW) Health Pathology, John Hunter Hospital, Newcastle, NSW, Australia
| | - Vilija G. Jokubaitis
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
| | - Rodney A. Lea
- School of Biomedical Science and Pharmacy, University of Newcastle, Newcastle, NSW, Australia
- Centre of Genomics and Personalised Health, School of Biomedical Sciences, Queensland University of Technology, Kelvin Grove, QLD, Australia
| | - Jeannette Lechner-Scott
- Hunter Medical Research Institute, Immune Health research program, Newcastle, NSW, Australia
- Department of Neurology, John Hunter Hospital, Newcastle, NSW, Australia
- School of Medicine and Public Health, University of Newcastle, Newcastle, NSW, Australia
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2
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Bingen JM, Clark LV, Band MR, Munzir I, Carrithers MD. Differential DNA methylation associated with multiple sclerosis and disease modifying treatments in an underrepresented minority population. Front Genet 2023; 13:1058817. [PMID: 36685876 PMCID: PMC9845287 DOI: 10.3389/fgene.2022.1058817] [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: 10/03/2022] [Accepted: 11/28/2022] [Indexed: 01/06/2023] Open
Abstract
Black and Hispanic American patients frequently develop earlier onset of multiple sclerosis (MS) and a more severe disease course that can be resistant to disease modifying treatments. The objectives were to identify differential methylation of genomic DNA (gDNA) associated with disease susceptibility and treatment responses in a cohort of MS patients from underrepresented minority populations. Patients with MS and controls with non-inflammatory neurologic conditions were consented and enrolled under an IRB-approved protocol. Approximately 64% of donors identified as Black or African American and 30% as White, Hispanic-Latino. Infinium MethylationEPIC bead arrays were utilized to measure epigenome-wide gDNA methylation of whole blood. Data were analyzed in the presence and absence of adjustments for unknown covariates in the dataset, some of which corresponded to disease modifying treatments. Global patterns of differential methylation associated with MS were strongest for those probes that showed relative demethylation of loci with lower M values. Pathway analysis revealed unexpected associations with shigellosis and amoebiasis. Enrichment analysis revealed an over-representation of probes in enhancer regions and an under-representation in promoters. In the presence of adjustments for covariates that included disease modifying treatments, analysis revealed 10 differentially methylated regions (DMR's) with an FDR <1E-77. Five of these genes (ARID5B, BAZ2B, RABGAP1, SFRP2, WBP1L) are associated with cancer risk and cellular differentiation and have not been previously identified in MS studies. Hierarchical cluster and multi-dimensional scaling analysis of differential DNA methylation at 147 loci within those DMR's was sufficient to differentiate MS donors from controls. In the absence of corrections for disease modifying treatments, differential methylation in patients treated with dimethyl fumarate was associated with immune regulatory pathways that regulate cytokine and chemokine signaling, axon guidance, and adherens junctions. These results demonstrate possible associations of gastrointestinal pathogens and regulation of cellular differentiation with MS susceptibility in our patient cohort. This work further suggests that analyses can be performed in the presence and absence of corrections for immune therapies. Because of their high representation in our patient cohort, these results may be of specific relevance in the regulation of disease susceptibility and treatment responses in Black and Hispanic Americans.
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Affiliation(s)
- Jeremy M. Bingen
- Neurology, University of Illinois College of Medicine, Chicago, IL, United States
- Physiology and Biophysics, University of Illinois College of Medicine, Chicago, IL, United States
| | - Lindsay V. Clark
- High Performance Biological Computing, and Roy J Carver Biotechnology Center, University of Illinois, Champaign, IL, United States
| | - Mark R. Band
- High Performance Biological Computing, and Roy J Carver Biotechnology Center, University of Illinois, Champaign, IL, United States
| | - Ilyas Munzir
- Neurology, University of Illinois College of Medicine, Chicago, IL, United States
| | - Michael D. Carrithers
- Neurology, University of Illinois College of Medicine, Chicago, IL, United States
- Physiology and Biophysics, University of Illinois College of Medicine, Chicago, IL, United States
- Neurology, Jesse Brown Veterans Administration Hospital, Chicago, IL, United States
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Campagna MP, Xavier A, Lea RA, Stankovich J, Maltby VE, Butzkueven H, Lechner-Scott J, Scott RJ, Jokubaitis VG. Whole-blood methylation signatures are associated with and accurately classify multiple sclerosis disease severity. Clin Epigenetics 2022; 14:194. [PMID: 36585691 PMCID: PMC9805090 DOI: 10.1186/s13148-022-01397-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 12/02/2022] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND The variation in multiple sclerosis (MS) disease severity is incompletely explained by genetics, suggesting genetic and environmental interactions are involved. Moreover, the lack of prognostic biomarkers makes it difficult for clinicians to optimise care. DNA methylation is one epigenetic mechanism by which gene-environment interactions can be assessed. Here, we aimed to identify DNA methylation patterns associated with mild and severe relapse-onset MS (RMS) and to test the utility of methylation as a predictive biomarker. METHODS We conducted an epigenome-wide association study between 235 females with mild (n = 119) or severe (n = 116) with RMS. Methylation was measured with the Illumina methylationEPIC array and analysed using logistic regression. To generate hypotheses about the functional consequence of differential methylation, we conducted gene set enrichment analysis using ToppGene. We compared the accuracy of three machine learning models in classifying disease severity: (1) clinical data available at baseline (age at onset and first symptoms) built using elastic net (EN) regression, (2) methylation data using EN regression and (3) a weighted methylation risk score of differentially methylated positions (DMPs) from the main analysis using logistic regression. We used a conservative 70:30 test:train split for classification modelling. A false discovery rate threshold of 0.05 was used to assess statistical significance. RESULTS Females with mild or severe RMS had 1472 DMPs in whole blood (839 hypermethylated, 633 hypomethylated in the severe group). Differential methylation was enriched in genes related to neuronal cellular compartments and processes, and B-cell receptor signalling. Whole-blood methylation levels at 1708 correlated CpG sites classified disease severity more accurately (machine learning model 2, AUC = 0.91) than clinical data (model 1, AUC = 0.74) or the wMRS (model 3, AUC = 0.77). Of the 1708 selected CpGs, 100 overlapped with DMPs from the main analysis at the gene level. These overlapping genes were enriched in neuron projection and dendrite extension, lending support to our finding that neuronal processes, rather than immune processes, are implicated in disease severity. CONCLUSION RMS disease severity is associated with whole-blood methylation at genes related to neuronal structure and function. Moreover, correlated whole-blood methylation patterns can assign disease severity in females with RMS more accurately than clinical data available at diagnosis.
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Affiliation(s)
- Maria Pia Campagna
- grid.1002.30000 0004 1936 7857Central Clinical School, Monash University, Melbourne, VIC Australia
| | - Alexandre Xavier
- grid.266842.c0000 0000 8831 109XHunter Medical Research Institute, University of Newcastle, Newcastle, NSW Australia
| | - Rodney A. Lea
- grid.1024.70000000089150953Queensland University of Technology, Brisbane, QLD Australia ,grid.1008.90000 0001 2179 088XUniversity of Melbourne, Melbourne, VIC Australia
| | - Jim Stankovich
- grid.1002.30000 0004 1936 7857Monash University, Melbourne, VIC Australia
| | - Vicki E. Maltby
- grid.266842.c0000 0000 8831 109XHunter Medical Research Institute, University of Newcastle, Newcastle, NSW Australia
| | - Helmut Butzkueven
- grid.1002.30000 0004 1936 7857Monash University, Melbourne, VIC Australia ,grid.1008.90000 0001 2179 088XUniversity of Melbourne, Melbourne, VIC Australia ,grid.416153.40000 0004 0624 1200Royal Melbourne Hospital, Melbourne, VIC Australia ,grid.414366.20000 0004 0379 3501Neurology Department, Eastern Health, Melbourne, VIC Australia ,grid.267362.40000 0004 0432 5259Neurology Department, Alfred Health, Melbourne, VIC Australia
| | - Jeannette Lechner-Scott
- grid.266842.c0000 0000 8831 109XHunter Medical Research Institute, University of Newcastle, Newcastle, NSW Australia ,grid.3006.50000 0004 0438 2042Neurology Department, John Hunter Hospital, Hunter New England Health, Newcastle, NSW Australia
| | - Rodney J. Scott
- grid.266842.c0000 0000 8831 109XSchool of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, NSW Australia ,Division of Molecular Medicine, New South Wales Health Pathology North, Newcastle, NSW Australia
| | - Vilija G. Jokubaitis
- grid.1002.30000 0004 1936 7857Monash University, Melbourne, VIC Australia ,grid.1008.90000 0001 2179 088XUniversity of Melbourne, Melbourne, VIC Australia ,grid.416153.40000 0004 0624 1200Royal Melbourne Hospital, Melbourne, VIC Australia ,grid.267362.40000 0004 0432 5259Neurology Department, Alfred Health, Melbourne, VIC Australia
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4
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Roostaei T, Klein HU, Ma Y, Felsky D, Kivisäkk P, Connor SM, Kroshilina A, Yung C, Kaskow BJ, Shao X, Rhead B, Ordovás JM, Absher DM, Arnett DK, Liu J, Patsopoulos N, Barcellos LF, Weiner HL, De Jager PL. Proximal and distal effects of genetic susceptibility to multiple sclerosis on the T cell epigenome. Nat Commun 2021; 12:7078. [PMID: 34873174 PMCID: PMC8648735 DOI: 10.1038/s41467-021-27427-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2020] [Accepted: 11/18/2021] [Indexed: 01/29/2023] Open
Abstract
Identifying the effects of genetic variation on the epigenome in disease-relevant cell types can help advance our understanding of the first molecular contributions of genetic susceptibility to disease onset. Here, we establish a genome-wide map of DNA methylation quantitative trait loci in CD4+ T-cells isolated from multiple sclerosis patients. Utilizing this map in a colocalization analysis, we identify 19 loci where the same haplotype drives both multiple sclerosis susceptibility and local DNA methylation. We also identify two distant methylation effects of multiple sclerosis susceptibility loci: a chromosome 16 locus affects PRDM8 methylation (a chromosome 4 region not previously associated with multiple sclerosis), and the aggregate effect of multiple sclerosis-associated variants in the major histocompatibility complex influences DNA methylation near PRKCA (chromosome 17). Overall, we present a new resource for a key cell type in inflammatory disease research and uncover new gene targets for the study of predisposition to multiple sclerosis.
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Affiliation(s)
- Tina Roostaei
- grid.21729.3f0000000419368729Center for Translational and Computational Neuroimmunology, Department of Neurology and the Taub Institute for Research on Alzheimer’s disease and the Aging brain, Columbia University Irving Medical Center, New York, NY USA
| | - Hans-Ulrich Klein
- grid.21729.3f0000000419368729Center for Translational and Computational Neuroimmunology, Department of Neurology and the Taub Institute for Research on Alzheimer’s disease and the Aging brain, Columbia University Irving Medical Center, New York, NY USA
| | - Yiyi Ma
- grid.21729.3f0000000419368729Center for Translational and Computational Neuroimmunology, Department of Neurology and the Taub Institute for Research on Alzheimer’s disease and the Aging brain, Columbia University Irving Medical Center, New York, NY USA
| | - Daniel Felsky
- grid.17063.330000 0001 2157 2938Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, University of Toronto, Toronto, ON Canada
| | - Pia Kivisäkk
- grid.32224.350000 0004 0386 9924Alzheimer’s Clinical and Translational Research Unit, Department of Neurology, Massachusetts General Hospital, Boston, MA USA
| | - Sarah M. Connor
- grid.21729.3f0000000419368729Center for Translational and Computational Neuroimmunology, Department of Neurology and the Taub Institute for Research on Alzheimer’s disease and the Aging brain, Columbia University Irving Medical Center, New York, NY USA
| | - Alexandra Kroshilina
- grid.21729.3f0000000419368729Center for Translational and Computational Neuroimmunology, Department of Neurology and the Taub Institute for Research on Alzheimer’s disease and the Aging brain, Columbia University Irving Medical Center, New York, NY USA
| | - Christina Yung
- grid.21729.3f0000000419368729Center for Translational and Computational Neuroimmunology, Department of Neurology and the Taub Institute for Research on Alzheimer’s disease and the Aging brain, Columbia University Irving Medical Center, New York, NY USA
| | - Belinda J. Kaskow
- grid.62560.370000 0004 0378 8294Ann Romney Center for Neurologic Diseases, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA USA
| | - Xiaorong Shao
- grid.47840.3f0000 0001 2181 7878Genetic Epidemiology and Genomics Laboratory, University of California, Berkeley, CA USA
| | - Brooke Rhead
- grid.47840.3f0000 0001 2181 7878Genetic Epidemiology and Genomics Laboratory, University of California, Berkeley, CA USA
| | - José M. Ordovás
- grid.429997.80000 0004 1936 7531Jean Mayer US Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA USA
| | - Devin M. Absher
- grid.417691.c0000 0004 0408 3720HudsonAlpha Institute for Biotechnology, Huntsville, AL USA
| | - Donna K. Arnett
- grid.266539.d0000 0004 1936 8438College of Public Health, University of Kentucky, Lexington, KY USA
| | - Jia Liu
- grid.212340.60000000122985718Advanced Science Research Center at the Graduate Center, Neuroscience Initiative, City University of New York, New York, NY USA
| | - Nikolaos Patsopoulos
- grid.62560.370000 0004 0378 8294Ann Romney Center for Neurologic Diseases, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA USA
| | - Lisa F. Barcellos
- grid.47840.3f0000 0001 2181 7878Genetic Epidemiology and Genomics Laboratory, University of California, Berkeley, CA USA
| | - Howard L. Weiner
- grid.62560.370000 0004 0378 8294Ann Romney Center for Neurologic Diseases, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA USA
| | - Philip L. De Jager
- grid.21729.3f0000000419368729Center for Translational and Computational Neuroimmunology, Department of Neurology and the Taub Institute for Research on Alzheimer’s disease and the Aging brain, Columbia University Irving Medical Center, New York, NY USA
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5
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Campagna MP, Xavier A, Lechner-Scott J, Maltby V, Scott RJ, Butzkueven H, Jokubaitis VG, Lea RA. Epigenome-wide association studies: current knowledge, strategies and recommendations. Clin Epigenetics 2021; 13:214. [PMID: 34863305 PMCID: PMC8645110 DOI: 10.1186/s13148-021-01200-8] [Citation(s) in RCA: 60] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 11/19/2021] [Indexed: 02/06/2023] Open
Abstract
The aetiology and pathophysiology of complex diseases are driven by the interaction between genetic and environmental factors. The variability in risk and outcomes in these diseases are incompletely explained by genetics or environmental risk factors individually. Therefore, researchers are now exploring the epigenome, a biological interface at which genetics and the environment can interact. There is a growing body of evidence supporting the role of epigenetic mechanisms in complex disease pathophysiology. Epigenome-wide association studies (EWASes) investigate the association between a phenotype and epigenetic variants, most commonly DNA methylation. The decreasing cost of measuring epigenome-wide methylation and the increasing accessibility of bioinformatic pipelines have contributed to the rise in EWASes published in recent years. Here, we review the current literature on these EWASes and provide further recommendations and strategies for successfully conducting them. We have constrained our review to studies using methylation data as this is the most studied epigenetic mechanism; microarray-based data as whole-genome bisulphite sequencing remains prohibitively expensive for most laboratories; and blood-based studies due to the non-invasiveness of peripheral blood collection and availability of archived DNA, as well as the accessibility of publicly available blood-cell-based methylation data. Further, we address multiple novel areas of EWAS analysis that have not been covered in previous reviews: (1) longitudinal study designs, (2) the chip analysis methylation pipeline (ChAMP), (3) differentially methylated region (DMR) identification paradigms, (4) methylation quantitative trait loci (methQTL) analysis, (5) methylation age analysis and (6) identifying cell-specific differential methylation from mixed cell data using statistical deconvolution.
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Affiliation(s)
- Maria Pia Campagna
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
| | - Alexandre Xavier
- Centre for Information Based Medicine, Hunter Medical Research Institute, Newcastle, Australia
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, Australia
| | - Jeannette Lechner-Scott
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, Australia
- Department of Neurology, Division of Medicine, John Hunter Hospital, Newcastle, Australia
| | - Vicky Maltby
- Centre for Information Based Medicine, Hunter Medical Research Institute, Newcastle, Australia
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, Australia
| | - Rodney J Scott
- Centre for Information Based Medicine, Hunter Medical Research Institute, Newcastle, Australia
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, Australia
- Division of Molecular Medicine, New South Wales Health Pathology North, Newcastle, Australia
| | - Helmut Butzkueven
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
- Department of Neurology, Alfred Health, Melbourne, Australia
| | - Vilija G Jokubaitis
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
- Department of Neurology, Alfred Health, Melbourne, Australia
| | - Rodney A Lea
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, Australia.
- Centre for Genomics and Personalised Health, School of Biomedical Sciences, Queensland University of Technology, Brisbane, Australia.
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6
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Maltby VE, Lea RA, Monif M, Fabis-Pedrini MJ, Buzzard K, Kalincik T, Kermode AG, Taylor B, Hodgkinson S, McCombe P, Butzkueven H, Barnett M, Lechner-Scott J. Efficacy of Cladribine Tablets as a Treatment for People With Multiple Sclerosis: Protocol for the CLOBAS Study (Cladribine, a Multicenter, Long-term Efficacy and Biomarker Australian Study). JMIR Res Protoc 2021; 10:e24969. [PMID: 34665152 PMCID: PMC8564661 DOI: 10.2196/24969] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Revised: 05/04/2021] [Accepted: 05/28/2021] [Indexed: 01/26/2023] Open
Abstract
Background Cladribine tablets (marketed as Mavenclad) are a new oral therapy, which has recently been listed on the pharmaceutical benefits scheme in Australia for the treatment of relapsing multiple sclerosis (MS). The current dosing schedule is for 2 courses given a year apart, which has been shown to be effective for treatment of MS for up to 4 years in 75% of patients (based on annualized relapse rate). However, the reinitiation of therapy after year 4 has not been studied. Objective This study aims to evaluate the safety and efficacy of cladribine tablets over a 6-year period, according to no evidence of disease activity 3. Methods This will be a multicenter, 6-year, phase IV, low interventional, observational study that incorporates clinical, hematological, biochemical, epigenetic, radiological and cognitive biomarkers of disease. Participants considered for treatment with cladribine as part of their routine clinical care will be consented to take part in the study. They will be monitored at regular intervals during the initial course of medication administration in years 1 and 2. After year 3, patients will have the option of redosing, if clinically indicated, or to switch to another disease-modifying therapy. Throughout the duration of the study, we will assess blood-based biomarkers including lymphocyte subsets, serum neurofilament light chain, DNA methylation, and RNA analysis as well as magnetic resonance imaging findings (brain volume and/or lesion load) and cognitive performance. Results This study has been approved by the Hunter New England Local Health District Human Research Ethics Committee. Recruitment began in March of 2019 and was completed by June 2021. Conclusions This will be the first long-term efficacy trial of cladribine, which offers reinitiation of therapy in the 3rd year, based on disease activity, after the initial 2 courses. We expect that this study will indicate whether any of the assessed biomarkers can be used to predict treatment efficacy or the need for future reinitiation of cladribine in people with MS. Trial Registration This study is registered with the Australian and New Zealand Clinical Trials Registry (ACTRN12619000257167) with Universal Trial Number (U1111-1228-2165). International Registered Report Identifier (IRRID) DERR1-10.2196/24969
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Affiliation(s)
- Vicki E Maltby
- Department of Neurology, John Hunter Hospital, New Lambton Heights, Australia.,School for Medicine and Public Health, University of Newcastle, Callaghan, Australia.,Hunter Medical Research Institute, New Lambton Heights, Australia
| | - Rodney A Lea
- School for Medicine and Public Health, University of Newcastle, Callaghan, Australia.,Hunter Medical Research Institute, New Lambton Heights, Australia.,Institute of Health and Biomedical Innovations, Genomics Research Centre, Queensland University of Technology, Kelvin Grove, Australia
| | - Mastura Monif
- Department of Neurosciences, Eastern Health Clinical School, Monash University, Box Hill Hospital, Melbourne, Australia.,Department of Neurology, Alfred Health, Melbourne, Australia.,Department of Neurology, Melbourne Multiple Sclerosis Centre, Melbourne Health, Melbourne, Australia
| | - Marzena J Fabis-Pedrini
- Centre for Neuromuscular and Neurological Disorders, Perron Institute for Neurological and Translational Science, University of Western Australia, Perth, Australia
| | - Katherine Buzzard
- Department of Neurosciences, Eastern Health Clinical School, Monash University, Box Hill Hospital, Melbourne, Australia.,Department of Neurology, Melbourne Multiple Sclerosis Centre, Melbourne Health, Melbourne, Australia
| | - Tomas Kalincik
- Department of Neurology, Melbourne Multiple Sclerosis Centre, Melbourne Health, Melbourne, Australia.,Clinical Outcomes Research (CORe) Unit, Department of Medicine, University of Melbourne, Melbourne, Australia
| | - Allan G Kermode
- Centre for Neuromuscular and Neurological Disorders, Perron Institute for Neurological and Translational Science, University of Western Australia, Perth, Australia.,Institute for Immunology and Infectious Disease, Murdoch University, Perth, Australia
| | - Bruce Taylor
- Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia
| | - Suzanne Hodgkinson
- Department of Medicine, University of New South Wales, Sydney, Australia.,Department of Neurology, Liverpool Hospital, Sydney, Australia.,Immune Tolerance Laboratory, Ingham Institute, Sydney, Australia
| | - Pamela McCombe
- Centre for Clinical Research, University of Queensland, Brisbane, Australia
| | - Helmut Butzkueven
- Department of Neurology, Alfred Health, Melbourne, Australia.,Clinical Outcomes Research (CORe) Unit, Department of Medicine, University of Melbourne, Melbourne, Australia
| | - Michael Barnett
- Brain and Mind Centre, University of Sydney, Sydney, Australia.,Sydney Neuroimaging Analysis Centre, Sydney, Australia
| | - Jeannette Lechner-Scott
- Department of Neurology, John Hunter Hospital, New Lambton Heights, Australia.,School for Medicine and Public Health, University of Newcastle, Callaghan, Australia.,Hunter Medical Research Institute, New Lambton Heights, Australia
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7
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Kiselev IS, Kulakova OG, Boyko AN, Favorova OO. DNA Methylation As an Epigenetic Mechanism in the Development of Multiple Sclerosis. Acta Naturae 2021; 13:45-57. [PMID: 34377555 PMCID: PMC8327151 DOI: 10.32607/actanaturae.11043] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Accepted: 09/24/2020] [Indexed: 12/13/2022] Open
Abstract
The epigenetic mechanisms of gene expression regulation are a group of the key cellular and molecular pathways that lead to inherited alterations in genes' activity without changing their coding sequence. DNA methylation at the C5 position of cytosine in CpG dinucleotides is amongst the central epigenetic mechanisms. Currently, the number of studies that are devoted to the identification of methylation patterns specific to multiple sclerosis (MS), a severe chronic autoimmune disease of the central nervous system, is on a rapid rise. However, the issue of the contribution of DNA methylation to the development of the different clinical phenotypes of this highly heterogeneous disease has only begun to attract the attention of researchers. This review summarizes the data on the molecular mechanisms underlying DNA methylation and the MS risk factors that can affect the DNA methylation profile and, thereby, modulate the expression of the genes involved in the disease's pathogenesis. The focus of our attention is centered on the analysis of the published data on the differential methylation of DNA from various biological samples of MS patients obtained using both the candidate gene approach and high-throughput methods.
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Affiliation(s)
- I. S. Kiselev
- Pirogov Russian National Research Medical University, Moscow, 117997 Russia
| | - O. G. Kulakova
- Pirogov Russian National Research Medical University, Moscow, 117997 Russia
| | - A. N. Boyko
- Pirogov Russian National Research Medical University, Moscow, 117997 Russia
| | - O. O. Favorova
- Pirogov Russian National Research Medical University, Moscow, 117997 Russia
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Wei H, Wang JY. Role of Polymeric Immunoglobulin Receptor in IgA and IgM Transcytosis. Int J Mol Sci 2021; 22:ijms22052284. [PMID: 33668983 PMCID: PMC7956327 DOI: 10.3390/ijms22052284] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Revised: 02/20/2021] [Accepted: 02/22/2021] [Indexed: 12/13/2022] Open
Abstract
Transcytosis of polymeric IgA and IgM from the basolateral surface to the apical side of the epithelium and subsequent secretion into mucosal fluids are mediated by the polymeric immunoglobulin receptor (pIgR). Secreted IgA and IgM have vital roles in mucosal immunity in response to pathogenic infections. Binding and recognition of polymeric IgA and IgM by pIgR require the joining chain (J chain), a small protein essential in the formation and stabilization of polymeric Ig structures. Recent studies have identified marginal zone B and B1 cell-specific protein (MZB1) as a novel regulator of polymeric IgA and IgM formation. MZB1 might facilitate IgA and IgM transcytosis by promoting the binding of J chain to Ig. In this review, we discuss the roles of pIgR in transcytosis of IgA and IgM, the roles of J chain in the formation of polymeric IgA and IgM and recognition by pIgR, and focus particularly on recent progress in understanding the roles of MZB1, a molecular chaperone protein.
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Affiliation(s)
- Hao Wei
- Department of Immunology, School of Basic Medical Sciences, Fudan University, Shanghai 200032, China;
| | - Ji-Yang Wang
- Department of Immunology, School of Basic Medical Sciences, Fudan University, Shanghai 200032, China;
- Department of Clinical Immunology, Children’s Hospital of Fudan University, Shanghai 201102, China
- Department of Microbiology and Immunology, College of Basic Medical Sciences, Zhengzhou University, Zhengzhou 450001, Henan, China
- Correspondence: ; Tel.: +86-(21)-54237957
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