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DNA methylation profiles of four immune cell types from MS patients and healthy controls

ABSTRACT: DNA methylation profiles of four immune cell types from MS patients and healthy controls

PROVIDER: PRJNA727170 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR14417000.fastq.gz	Fastqsanger.gz
	SRR14417000_1.fastq.gz	Fastqsanger.gz
	SRR14417000_2.fastq.gz	Fastqsanger.gz
	SRR14417001.fastq.gz	Fastqsanger.gz
	SRR14417001_1.fastq.gz	Fastqsanger.gz

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DNA methylation profiles of four immune cell types from MS patients and healthy controls

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Project description:Multiple Sclerosis (MS) is an immune-mediated chronic inflammatory disease affecting the central nervous system. The cause of MS is not known and the mechanism of IFN-beta, a disease-modifying treatment (DMT) approved for MS, is not well-understood. Oligonucleotide microarrays were used to study gene expression in plasmacytoid denditic cells (pDCs) which are antigen-presenting cells implicated in MS pathogenesis. We analyzed gene expression in pDCs of healthy controls, untreated and IFN-beta treated MS patients. We were able to identify 60 genes which were abnormally expressed in untreated MS patients and were corrected after treatment with IFN-beta.

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Project description:Background Multiple Sclerosis (MS) is a chronic inflammatory disease and a leading cause of progressive neurological disability among young adults. DNA methylation, which intersects genes and environment to control cellular functions on a molecular level, may provide insights into MS pathogenesis. Methods We measured DNA methylation in CD4+ T cells (n=31), CD8+ T cells (n=28), CD14+ monocytes (n=35) and CD19+ B cells (n=27) from relapsing-remitting (RRMS), secondary progressive (SPMS) patients and healthy controls (HC) using Infinium HumanMethylation450 arrays. Monocyte (n=25) and whole blood (n=275) cohorts were used for validations. Findings B cells from MS patients displayed most significant differentially methylated positions (DMPs), followed by monocytes, while only few DMPs were detected in T cells. We implemented a non-parametric combination framework (omicsNPC) to increase discovery power by combining evidence from all four cell types. Identified shared DMPs co-localized at MS risk loci and clustered into distinct groups. Functional exploration of changes discriminating RRMS and SPMS from HC implicated lymphocyte signaling, T cell activation and migration. SPMS-specific changes, on the other hand, implicated myeloid cell functions and metabolism. Interestingly, neuronal and neurodegenerative genes and pathways were also specifically enriched in the SPMS cluster. Interpretation We utilized a statistical framework (omicsNPC) that combines multiple layers of evidence to identify DNA methylation changes that provide new insights into MS pathogenesis in general, and disease progression, in particular.

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