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Differential DNA methylation in Multiple Sclerosis

ABSTRACT: Differential DNA methylation in Multiple Sclerosis

PROVIDER: PRJNA417506 | ENA |

REPOSITORIES: ENA

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Differential DNA methylation in Multiple Sclerosis

Project description:Genome-wide DNA methylation level was studied to determine whether multiple sclerosis patients (cases) has methylation differences comparing to normal controls in PBLs. We used Illumina HumanMethylation450 BeadChip array to determine the genome-wide DNA methylation difference in peripheral blood from multiple sclerosis patients (cases) and normal controls

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DNA methylation differences between multiple sclerosis and controls in frontal lobe white matter

Project description:Using the Illumina 450K array and a stringent statistical analysis with age and gender correction, we report genome-wide differences in DNA methylation between pathology-free regions derived from human multiple sclerosis–affected and control brains. Differences were subtle, but widespread and reproducible in an independent validation cohort. The transcriptional consequences of differential DNA methylation were further defined by genome-wide RNA-sequencing analysis and validated in two independent cohorts. Genes regulating oligodendrocyte survival, such as BCL2L2 and NDRG1, were hypermethylated and expressed at lower levels in multiple sclerosis–affected brains than in controls, while genes related to proteolytic processing (for example, LGMN, CTSZ) were hypomethylated and expressed at higher levels. These results were not due to differences in cellular composition between multiple sclerosis and controls. Thus, epigenomic changes in genes affecting oligodendrocyte susceptibility to damage are detected in pathology-free areas of multiple sclerosis–affected brains.

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Deconvolution of whole blood DNA methylomes reveals immune cell type-specific differential methylation in Multiple Sclerosis

Project description:Whole blood is a highly convenient and informative tissue from which to sample DNA and RNA in epigenomic and functional genomic studies, but it is comprised of multiple distinct cell types and this complexity significantly impairs our ability to interpret downstream differential methylation and/or differential expression results. In this multiple sclerosis (MS)-focused study we utilised an application of current statistical deconvolution methods to interrogate whole blood DNA methylation data thereby enabling the methylome of several immune cell types to be analysed independently. Methylome profiling on cell type-purified blood samples revealed optimal CpG sets for use as robust immune cell markers in the statistical deconvolution process. We show that it is possible to identify differentially methylated (DM) loci in a cell type specific manner using statistical deconvolution. Finally, we demonstrate that deconvolution improved the biological relevance and interpretability of our DM results, significantly enhancing concordance of the identified DM loci with loci previously shown to be genetically or epigenetically associated with MS.

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Identification of differential DNA methylation associated with multiple sclerosis: a family-based study

Project description:Multiple Sclerosis (MS) is known to be caused by a genetic predisposition triggered by environmental factors. Despite the knowledge of genetic factors and environmental agents involved, it is largely unclear how they interact. Epigenetics, particularly DNA methylation, represents a model for environmental factors to influence the genome. In this paper, we studied 26 affected and 26 unaffected relatives from 8 MS multiplex families (≥ 3 affected relatives) as part of a multicentric Italian cohort study using Methylated DNA immunoprecipitation sequencing (MeDIP-Seq) run on an Illumina® HiSeq 2500 (2x100 bp). Technical validation in 6/8 of the original families and biological replication in 2 additional families (FDR < 0.1 and a concordant fold change, FC) were performed in suggestive differentially methylated regions (DMRs) between affected and unaffected relatives using SeqCap Epi Choice Enrichment (Roche®). Evidence of association from MeDIP-Seq across 8 families was combined with aggregation statistics, separately for hypo- and hyper-methylated regions with concordant FC in ≥ 6/8 families, yielding 162 DMRs at FDR ≤ 0.1. Technical validation and biological replication led to 2 hypomethylated regions, which point to NTM and BAI3 genes, and 2 hypermethylated regions in PIK3R1 and CAPN13 (mean size: 3.1 kb). Multiplex families represent a privileged setting for the study of regions of differential methylation as they reduce the impact of potential confounders like shared genetics and environmental factors. We identified 4 novel regions which contain genes of potential interest that need to be tested in larger cohorts of patients.

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