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Tiane A, Schepers M, Reijnders RA, van Veggel L, Chenine S, Rombaut B, Dempster E, Verfaillie C, Wasner K, Grünewald A, Prickaerts J, Pishva E, Hellings N, van den Hove D, Vanmierlo T. From methylation to myelination: epigenomic and transcriptomic profiling of chronic inactive demyelinated multiple sclerosis lesions. Acta Neuropathol 2023; 146:283-299. [PMID: 37286732 PMCID: PMC10328906 DOI: 10.1007/s00401-023-02596-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 06/01/2023] [Accepted: 06/01/2023] [Indexed: 06/09/2023]
Abstract
In the progressive phase of multiple sclerosis (MS), the hampered differentiation capacity of oligodendrocyte precursor cells (OPCs) eventually results in remyelination failure. We have previously shown that DNA methylation of Id2/Id4 is highly involved in OPC differentiation and remyelination. In this study, we took an unbiased approach by determining genome-wide DNA methylation patterns within chronically demyelinated MS lesions and investigated how certain epigenetic signatures relate to OPC differentiation capacity. We compared genome-wide DNA methylation and transcriptional profiles between chronically demyelinated MS lesions and matched normal-appearing white matter (NAWM), making use of post-mortem brain tissue (n = 9/group). DNA methylation differences that inversely correlated with mRNA expression of their corresponding genes were validated for their cell-type specificity in laser-captured OPCs using pyrosequencing. The CRISPR-dCas9-DNMT3a/TET1 system was used to epigenetically edit human-iPSC-derived oligodendrocytes to assess the effect on cellular differentiation. Our data show hypermethylation of CpGs within genes that cluster in gene ontologies related to myelination and axon ensheathment. Cell type-specific validation indicates a region-dependent hypermethylation of MBP, encoding for myelin basic protein, in OPCs obtained from white matter lesions compared to NAWM-derived OPCs. By altering the DNA methylation state of specific CpGs within the promotor region of MBP, using epigenetic editing, we show that cellular differentiation and myelination can be bidirectionally manipulated using the CRISPR-dCas9-DNMT3a/TET1 system in vitro. Our data indicate that OPCs within chronically demyelinated MS lesions acquire an inhibitory phenotype, which translates into hypermethylation of crucial myelination-related genes. Altering the epigenetic status of MBP can restore the differentiation capacity of OPCs and possibly boost (re)myelination.
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Affiliation(s)
- Assia Tiane
- Department of Neuroscience, Biomedical Research Institute, Faculty of Medicine and Life Sciences, Hasselt University, Hasselt, Belgium
- Department Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
- University MS Center (UMSC) Hasselt, Pelt, Belgium
| | - Melissa Schepers
- Department of Neuroscience, Biomedical Research Institute, Faculty of Medicine and Life Sciences, Hasselt University, Hasselt, Belgium
- Department Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
- University MS Center (UMSC) Hasselt, Pelt, Belgium
| | - Rick A. Reijnders
- Department Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Lieve van Veggel
- Department of Neuroscience, Biomedical Research Institute, Faculty of Medicine and Life Sciences, Hasselt University, Hasselt, Belgium
- Department Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
- University MS Center (UMSC) Hasselt, Pelt, Belgium
| | - Sarah Chenine
- Department of Neuroscience, Biomedical Research Institute, Faculty of Medicine and Life Sciences, Hasselt University, Hasselt, Belgium
- Department Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
- University MS Center (UMSC) Hasselt, Pelt, Belgium
| | - Ben Rombaut
- Department of Neuroscience, Biomedical Research Institute, Faculty of Medicine and Life Sciences, Hasselt University, Hasselt, Belgium
- Department Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
- University MS Center (UMSC) Hasselt, Pelt, Belgium
| | - Emma Dempster
- Institute of Biomedical and Clinical Sciences, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Catherine Verfaillie
- Stem Cell Institute, Department of Development and Regeneration, KU Leuven, Leuven, Belgium
| | - Kobi Wasner
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Anne Grünewald
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
- Institute of Neurogenetics, University of Lübeck, Lübeck, Germany
| | - Jos Prickaerts
- Department Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Ehsan Pishva
- Department Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Institute of Biomedical and Clinical Sciences, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Niels Hellings
- University MS Center (UMSC) Hasselt, Pelt, Belgium
- Department of Immunology and Infection, Biomedical Research Institute, Faculty of Medicine and Life Sciences, Hasselt University, Hasselt, Belgium
| | - Daniel van den Hove
- Department Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Department of Psychiatry, Psychosomatics and Psychotherapy, University of Wuerzburg, Würzburg, Germany
| | - Tim Vanmierlo
- Department of Neuroscience, Biomedical Research Institute, Faculty of Medicine and Life Sciences, Hasselt University, Hasselt, Belgium
- Department Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
- University MS Center (UMSC) Hasselt, Pelt, Belgium
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Al Jowf GI, Ahmed ZT, Reijnders RA, de Nijs L, Eijssen LMT. To Predict, Prevent, and Manage Post-Traumatic Stress Disorder (PTSD): A Review of Pathophysiology, Treatment, and Biomarkers. Int J Mol Sci 2023; 24:ijms24065238. [PMID: 36982313 PMCID: PMC10049301 DOI: 10.3390/ijms24065238] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 02/28/2023] [Accepted: 03/07/2023] [Indexed: 03/11/2023] Open
Abstract
Post-traumatic stress disorder (PTSD) can become a chronic and severely disabling condition resulting in a reduced quality of life and increased economic burden. The disorder is directly related to exposure to a traumatic event, e.g., a real or threatened injury, death, or sexual assault. Extensive research has been done on the neurobiological alterations underlying the disorder and its related phenotypes, revealing brain circuit disruption, neurotransmitter dysregulation, and hypothalamic–pituitary–adrenal (HPA) axis dysfunction. Psychotherapy remains the first-line treatment option for PTSD given its good efficacy, although pharmacotherapy can also be used as a stand-alone or in combination with psychotherapy. In order to reduce the prevalence and burden of the disorder, multilevel models of prevention have been developed to detect the disorder as early as possible and to reduce morbidity in those with established diseases. Despite the clinical grounds of diagnosis, attention is increasing to the discovery of reliable biomarkers that can predict susceptibility, aid diagnosis, or monitor treatment. Several potential biomarkers have been linked with pathophysiological changes related to PTSD, encouraging further research to identify actionable targets. This review highlights the current literature regarding the pathophysiology, disease development models, treatment modalities, and preventive models from a public health perspective, and discusses the current state of biomarker research.
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Affiliation(s)
- Ghazi I. Al Jowf
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Faculty of Health, Medicine and Life Sciences, Maastricht University Medical Centre, 6200 MD Maastricht, The Netherlands
- Department of Public Health, College of Applied Medical Sciences, King Faisal University, Al-Ahsa 31982, Saudi Arabia
- European Graduate School of Neuroscience, Maastricht University, 6200 MD Maastricht, The Netherlands
- Correspondence: (G.I.A.J.); (L.M.T.E.)
| | - Ziyad T. Ahmed
- College of Medicine, Sulaiman Al Rajhi University, Al-Bukairyah 52726, Saudi Arabia
| | - Rick A. Reijnders
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Faculty of Health, Medicine and Life Sciences, Maastricht University Medical Centre, 6200 MD Maastricht, The Netherlands
- European Graduate School of Neuroscience, Maastricht University, 6200 MD Maastricht, The Netherlands
| | - Laurence de Nijs
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Faculty of Health, Medicine and Life Sciences, Maastricht University Medical Centre, 6200 MD Maastricht, The Netherlands
- European Graduate School of Neuroscience, Maastricht University, 6200 MD Maastricht, The Netherlands
| | - Lars M. T. Eijssen
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Faculty of Health, Medicine and Life Sciences, Maastricht University Medical Centre, 6200 MD Maastricht, The Netherlands
- European Graduate School of Neuroscience, Maastricht University, 6200 MD Maastricht, The Netherlands
- Department of Bioinformatics—BiGCaT, School of Nutrition and Translational Research in Metabolism (NUTRIM), Faculty of Health, Medicine and Life Sciences, Maastricht University, 6200 MD Maastricht, The Netherlands
- Correspondence: (G.I.A.J.); (L.M.T.E.)
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Harvey J, Reijnders RA, Cavill R, Duits A, Köhler S, Eijssen LM, Rutten BP, Shireby G, Torkamani A, Creese B, Leentjens AF, Lunnon K, Pishva E. Machine learning‐based prediction of cognitive outcomes in de novo Parkinson's disease. Alzheimers Dement 2022. [DOI: 10.1002/alz.067067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
| | | | | | | | - Sebastian Köhler
- School for Mental Health and Neuroscience, Maastricht University Medical Center Maastricht Netherlands
| | | | | | | | - Ali Torkamani
- Scripps Research Translational Institute La Jolla CA USA
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Harvey J, Reijnders RA, Cavill R, Duits A, Köhler S, Eijssen L, Rutten BPF, Shireby G, Torkamani A, Creese B, Leentjens AFG, Lunnon K, Pishva E. Machine learning-based prediction of cognitive outcomes in de novo Parkinson's disease. NPJ Parkinsons Dis 2022; 8:150. [PMID: 36344548 PMCID: PMC9640625 DOI: 10.1038/s41531-022-00409-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Accepted: 10/11/2022] [Indexed: 11/09/2022] Open
Abstract
Cognitive impairment is a debilitating symptom in Parkinson's disease (PD). We aimed to establish an accurate multivariate machine learning (ML) model to predict cognitive outcome in newly diagnosed PD cases from the Parkinson's Progression Markers Initiative (PPMI). Annual cognitive assessments over an 8-year time span were used to define two cognitive outcomes of (i) cognitive impairment, and (ii) dementia conversion. Selected baseline variables were organized into three subsets of clinical, biofluid and genetic/epigenetic measures and tested using four different ML algorithms. Irrespective of the ML algorithm used, the models consisting of the clinical variables performed best and showed better prediction of cognitive impairment outcome over dementia conversion. We observed a marginal improvement in the prediction performance when clinical, biofluid, and epigenetic/genetic variables were all included in one model. Several cerebrospinal fluid measures and an epigenetic marker showed high predictive weighting in multiple models when included alongside clinical variables.
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Affiliation(s)
- Joshua Harvey
- Medical School, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Rick A Reijnders
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, The Netherlands
| | - Rachel Cavill
- Department of Advanced Computing Sciences, FSE, Maastricht University, Maastricht, The Netherlands
| | - Annelien Duits
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, The Netherlands
- Department of Medical Psychology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Sebastian Köhler
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, The Netherlands
| | - Lars Eijssen
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, The Netherlands
- Department of Bioinformatics-BiGCaT, School of Nutrition and Translational Research in Metabolism (NUTRIM), Maastricht University, Maastricht, The Netherlands
| | - Bart P F Rutten
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, The Netherlands
| | - Gemma Shireby
- Medical School, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Ali Torkamani
- Department of Integrative Structural and Computational Biology, Scripps Research, La Jolla, CA, 92037, USA
| | - Byron Creese
- Medical School, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Albert F G Leentjens
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, The Netherlands
| | - Katie Lunnon
- Medical School, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Ehsan Pishva
- Medical School, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK.
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, The Netherlands.
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