| Literature DB >> 31937331 |
Naiara Celarain1, Jordi Tomas-Roig2.
Abstract
Multiple sclerosis (MS) is an autoimmune and demyelinating disease of the central nervous system characterised by incoordination, sensory loss, weakness, changes in bladder capacity and bowel function, fatigue and cognitive impairment, creating a significant socioeconomic burden. The pathogenesis of MS involves both genetic susceptibility and exposure to distinct environmental risk factors. The gene x environment interaction is regulated by epigenetic mechanisms. Epigenetics refers to a complex system that modifies gene expression without altering the DNA sequence. The most studied epigenetic mechanism is DNA methylation. This epigenetic mark participates in distinct MS pathophysiological processes, including blood-brain barrier breakdown, inflammatory response, demyelination, remyelination failure and neurodegeneration. In this study, we also accurately summarised a list of environmental factors involved in the MS pathogenesis and its clinical course. A literature search was conducted using MEDLINE through PubMED and Scopus. In conclusion, an exhaustive study of DNA methylation might contribute towards new pharmacological interventions in MS by use of epigenetic drugs.Entities:
Keywords: DNA methylation; Environmental risk factors; Inflammation; Multiple sclerosis; Neurodegeneration
Year: 2020 PMID: 31937331 PMCID: PMC6961290 DOI: 10.1186/s12974-019-1667-1
Source DB: PubMed Journal: J Neuroinflammation ISSN: 1742-2094 Impact factor: 8.322
Fig. 1The underlying pathophysiological mechanism of MS. In the first instance, autoreactive CD4+ T cells are activated in the periphery by antigen presenting cells (APC) that present, in conjunction with class II MHC molecules, similar antigens to those synthesised by the CNS. (1) This interaction activates the differentiation of CD4+ T naïve cells into CD4+ T helper cells (Th). (2) Upon activation, Th produces interferon-gamma (IFN-γ), a cytokine responsible for recruiting CD8+ T cells, B cells and monocytes in the periphery. (3) These proinflammatory cells migrate to the blood–brain barrier (BBB) and pass into the CNS. Inside the brain, plasma B cells produce auto-antibodies against CNS self-antigens contributing to myelin sheath damage. This process is aggravated when infiltrated cytotoxic CD8+ T cells attack oligodendrocytes causing their destruction and neuronal death. Monocytes, on the other hand, increase local inflammatory response by releasing proinflammatory cytokines and contributing to demyelination through myelin phagocytosis. (4) In parallel, infiltrated CD4+ T cells are reactivated upon interaction with myelin fragments presented by resident APCs which favours (5) proinflammatory cytokines and chemokines release, (6) astrogliosis and microgliosis
Fig. 2DNA methylation metabolism. The addition of a methyl group to a naked cytosine is catalysed by DNMT (black arrow). 5-methylcytosine (5mC) is oxidised by TET enzymes to 5-hydroxymethylcytosine (5hmC) which can be further oxidised to 5-formylcytosine (5fC) and 5-carboxylcytosine (5caC) as indicated red arrows. In the deamination pathway (green arrows), AID or APOBEC can deaminate 5hmC to 5-hydroxymethyluracil (5hmU) or 5mC to thymine. Eventually, all these modified bases (5hmU, Thymine, 5fC, 5caC) are recognised by TDG and converted to naked cytosine through the base excision repair (BER) pathway (blue arrows)
DNA methylation changes in MS
| References | Comparison | Sample target | Method | Differentially methylated genes |
|---|---|---|---|---|
| [ | MS vs CTR | CD8+ T cells | Illumina 450K array | ERG, FTL, DCAF4, NCAPH2, CDKN1C, ZNF462, CBX7, MIR492, HPS1, SASH1, MYL3, KCNG1, DYDC2, MEGF10, SP5, LMO3, SLC12A7, MORN1, IGF2BP1, PLCB3, ABCC4, CREG2, CDC42BPB, UGT1A10, TMEM125, ARHGAP22, DACH1, OR8B12, TMEM8C, BAI1, EIF2S1, CRTAC1, DHX36, C19orf41, DLGAP2, TNXB, PRDM8, HEATR2, WHSC2, CAMTA1, ALK, KCNQ2, SCTR, RHEB, LOC202181, RRP9, KRT75, DGKE, PLD5, ZC3H14. |
| [ | RRMS vs CTR | CD4+ T cells | Illumina 450K array | MICA, MICB, HLA-DRB, MORN1, LCLAT1, PDCD1, MUC4, AHRR, ARSB, PCBD2, TGFBI, PCDHB13, PCDHB15, KIF25, CSGALNACT1, ADARB2, LDHAL6A, CORO1B, USP35, FUT4, ERC1, TCRA, PACS2, IL32, KCTD11, C17orf108, ARHGAP27, NPLOC4, SBNO2, GNG7, C21orf56, RIBC2. |
| [ | Myelinated vs demyelinated MS brains | Hippocampus | Illumina 450K array | MLLT4, PPIF, SCRT2, SNRNP40, ISLR2, MEF2A, PMEPA1, ABCA4, ADAMTS12, AHRR, BEST3, CASP7, CCL4L2, CPXM2, FBXW8, HLA-B, LOC145845, MEIS1, MGMT, MYO7A, NXN, PKP2, PQLC1, PSD3, SCN4B, SDK2, SMYD3, TGFBI, TMEM165, PON1, HDLBP, MKKS, TRIM26, TRPS1, KRTAP27-1, MGP, AJAP1, C1orf106, C2orf62, DSE, EIF2C2, GATA5, HLA-B, IGSF9B, INSC, KIAA1026, KIF25, LOC100292680, NFASC, RASA3, SDK1, SHISA2, SOLH, SORBS2, TAGLN3, TBX5, TM9SF1, TOP1MT, ZSCAN1, AKNA, EBPL, FLJ42709, HERC6, OR52M1, SFRP1, C22orf43, LOC285830, NAPEPLD, NHLH2, PLCH1, SERPINA9, SLFN13, TMEM132B, TTLL3, WDR81. |
| [ | SPMS vs CTR | PMBCs | Microarray dataset and RT-PCR | DNMT3A, GADD45A, GADD45B, MBD4, APOBEC3D, APOBEC4, GADD45G, TET1, TDG, APOBEC3C, APOBEC2, MBD2, MBD3, APOBEC3A, DNMT3B, APOBEC1, TET2, TET3. |
| [ | RRMS vs PPMS vs CTR | PMBCs | Illumina 450K array | |
| [ | Smoker vs non-smoker MS | PMBCs | Bisulphite Illumina Methylation 450k Beadchip | SRM, GNG12, GFI1, ANXA4, NFE2L2, ABLIM2, AHRR, SMIM3, CDKN1A, TPST1, CNTNAP2, SNTG1, MTSS1, PTK2, ZC3H3, ZMIZ1, PTGDR2, PRSS23, GRIK4, ETV6, RARG, LOC348021, CCDC88C, ITPK1, ANPEP, RARA, SMIM6, RECQL5, F2RL3, LINC00111, ACOT9. |
| [ | MS vs CTR | NAWM | Direct BS-sequencing | PAD2 |
| [ | RRMS vs CTR | cfDNA (whole blood) | BS-PCR sequencing assay | MBP3, WM1. |
| [ | MS vs CTR | NAWM | Bisulphite Illumina Methylation 450k Beadchip | ALDOA, ATP1A2, BCAR1, BRK1, CDK5, CORO1A, CSF3, DLC1, DTNBP1, FGD2, FMNL1, MLST8, MYBPC3, MYH6, MYH7, MYO1F, OBSCN, PDGFA, PRKCZ, SHC1, SIPA1L1, SSH3, TPM3, ADA, AGAP1, ALDOA, ARHGEF16, ATP1A1, ATP1A2, ATP1A4, ATP5H, BIN1, DAB2IP, DLC1, FGD2, LDHC, MACROD1, MLST8, MYBPC3, MYH6, MYH7, NME4, NT5C, PLXNB1, PTPRN2, RASA3, SEPT9, SIPA1L1, TBCD, TK1, ACSBG1, ACSL1, ACTR8, ADA, AGAP1, AGPAT1, AGRP, AKAP8, ALDH3A1, ALDOA, AMH, ANGPT2, APBB1IP, APEX, ARHGEF16, ATF6B, ATP11A, ATP1A1, ATP1A2, ATP1A4, ATP6V0E1, ATRIP, BBS2, BCAR1, BCL2L2, BIN1, BIRC5, BPI, BRD4, BRK1, C4B, CACNA1D, CASKIN1, CBX4, CCL17, CCL22, CD37, CD59, CDH1, CDK5, CHST3, CHURC1, CLASP1, CLIC5, CORO1A, CREB5, CRY2, CSF3, CSNK1E, CX3CL1, CXXC5, CYP21A2, DAB2IP, DAND5, DCPS, DHRS3, DLC1, DLL1, DOK4, DOT1L, DSCAML1, DTNBP1, DYRK1B, E2F6, E4F1, EDN2, EFS, ENTPD2, ERCC3, F7, FAM109A, FGD2, FGFR3, FMNL1, GBX1, GDF10, GPR114, GPR56, GTF2H1, GYLTL1B, HDAC11, HEG1, HEXIM1, HEXIM2, HIGD1A, HIST3H3, HLA-DMA, IL17RB, IL25, IL34, INO80E, INPP5J, INTS1, IRAK2, ITPKB, JARID2, LIMD1, LMF1, LPCAT1, MAB21L2, MADD, MAML3, MAP3K14, MAPK3, MBP, MCF2L, MED24, MEIS2, MLLT10, MLST8, MT1A, MT1E, MT1F, MT1G, MT1M, MT2A, MT4, MTCH1, MTSS1L, MUSK, MYBPC3, MYH6, MYH7, MYO1F, NARFL, NCOR2, NDRG1, NLRP3, NOTCH4, NR1H3, NUP210, OBSCN, OTX2, PABPN1, PAG1, PBX2, PCSK6, PDGFA, PEG10, PHF21A, PIK3R1, PLEKHG3, PLLP, PLXNB1, POLD4, POLR2C, POU2F1, PPARA, PPIL2, PPP1R13B, PPP4C, PRAM1, PRDM16, PRKCH, PRKCZ, PTGDS, PTPRN2, RAD9A, RAI1, RASA3, RBP1, RFX5, RIN2, RNF187, RPA1, RRM2, RXRA, SACS, SEMA4C, SETD1A, SHC1, SHISA5, SIPA1L1, SLC17A7, SLC22A17, SLC39A13, SLC7A8, SMAD6, SOX1, SOX8, SPI1, SPOCK2, SREBF1, SSH3, SSTR5, SUN1, TACC3, TBCD, TBX6, TEAD2, TEF, TEP1, THRA, TLN2, TNRC6C, TPM3, TRAF2, TSNARE1, UBE2L3, USP19, VAC14, WHSC1, WISP1, WISP2, WNK2, ZBTB47, ZFP1, ZIC1, ZNF135, ZNF256, ZNF329, ZNF362, ZNF414, ZNF418, ZNF488, ZNF606, ZNF664, ZNF687, ADAMDEC1, AIF1, AIRE, B2M, BPI, C1QA, C1QB, C1QC, C4BPA, C4BPB, CCR6, CD19, CD37, CD4, CD7, CD81, CFD, DLG1, FCER2, HAMP, HLA-DMA, HLA-DMB, HLA-DOA, HLA-DOB, HLA-DQA2, HLA-DQB2, HLA-F, IRF6, IRF8, IRF9, JAK1, JAK3, KYNU, LAG3, LAT, LBP, LCP2, LGMN, LST1, LTA, LTB, MBL2, MICB, NCR3, OSM, PSMB8, PTPN22, RARA, RNF31, SECTM1, SLAMF7, STXBP2, TAP1, TAP2, TAPBP, TNF, TNIP2, B2M, C1QA, C1QB, C1QC, C4BPA, C4BPB, DLG1, FCER2, HLA-DMA, LAG3, LTA, MBL2, NCR3, SLAMF7, TAP1, TAP2, TNF, B2M, C1QA, C1QB, C1QC, C4BPA, C4BPB, DLG1, FCER2, HLA-DMA, LAG3, LAT, LTA, MBL2, NCR3, SLAMF7, STXBP2, TAP1, TAP2, TNF, B2M, FCER2, HAMP, LAG3, MBL2, NCR3, SLAMF7, STXBP2, TAP1, TAP2, BHLHE23, CTSZ, DLG1, DLL1, DLX1, DLX2, EDARADD, EPHB4, FOXL2, GLI1, GNAS, HOXC11, HOXC13, HOXC4, HOXC8, HOXC9, HOXD10, HOXD11, HOXD13, HOXD3, HOXD4, HOXD8, HOXD9, MSX1, PHLDA2, PPP1R13L, PTCD2, RARA, RUNX3, SOX1, SOX8, TBX3, TEAD2, TGM1, TH, TNF, TWIST1, WNT2, ZIC1. |
| [ | RRMS and CTR | CD4+ T cells CD8+ T cells Whole blood | Illumina 450K array | |
| [ | RRMS vs PPMS vs SPMS vs CTR | Buffy coat | BS-sequencing | SHP-1 |
| [ | MS vs CTR | Whole blood PBMCs NAWM | Illumina 450K array | IL2RA |
| [ | MS treatment-naïve vs 1 year IFN-b vs CTR | PMBCs | BS-PCR sequencing assay | LINE-1 |
| [ | Discordant twins (RRMS vs CTR) | CD4+ T cells | RRBS | TMEM1, PEX14. |
| [ | RRMS(e)vs RRMS(r) vs CTR | Serum | BS-PCR sequencing assay | MOG |
| [ | RRMS vs CTR | cfDNA (serum) | BS-PCR sequencing assay | LINE-1 |
| [ | RRMS vs CTR | CD3+ T cells | BS-PCR sequencing assay | VDR |
| [ | RRMS(e) vs RRMS(r) vs CTR | cfDNA (plasma) | MethDet-56 microarray based assay | |
| [ | RRMS(e) vs RRMS(r) vs CTR | Whole Blood | Methylation-Specific Multiple Ligation Probe Amplification PCR | CDKN2A, SOCS1, RUNX3, NEUROG1. |
| [ | Discordant twins (MS vs CTR) | PMBCs CD4+ T cells | Bisulphite Illumina Methylation 450k Beadchip | TMEM232, SEMA3C, YWHAGI, ZBTB16, MRI1. |
| [ | RRMS and SPMS vs CTR | PMBCs | BS-PCR sequencing assay | PAD2 |
| [ | RRMS and SPMS vs CTR | PMBCs | EpiTyper assay | DNMT1, TET2 |
| [ | RRMS vs SPMS vs CTR | CD4+ T cells | Illumina 450K array | VMP1, MIR21 |
MS multiple sclerosis, CTR control, RRMS relapsing–remitting multiple sclerosis, PPMS primary progressive multiple sclerosis, SPMS secondary progressive multiple sclerosis, RRMS(e) RRMS in exacerbation, RRMS(r) RRMS in remission, cfDNA circulating-free DNA, PBMCs peripheral blood mononuclear cells, BS bisulphite, RRBS reduced representation bisulphite sequencing, NAWM normal appearing white matter
Fig. 3Risk factors of multiple sclerosis. MS pathogenesis is influenced by both genetic and environmental factors. Among the genetic factors, gender, disease-modifier genes, disease susceptibility genes and single nucleotide polymorphisms are remarkably important in prevalence and MS pathogenesis. In contrast, environmental factors such as smoking, vitamin D deficiency, organic solvents and pollutants exposure, diet style, Epstein Barr infection, dysbiosis of the gut microbiota, lack of exercise and stress are critically associated with MS susceptibility and progression
List of metabolites released by microbiota
| Metabolite | Effect on DNA methylation |
|---|---|
| p-Cresol | It induces the expression of DNA methyltransferases 1, 3a, and 3b and it is associated with CpG hypermethylation of Klotho gene [ |
| Hydrogen sulphide (H2S) | Involved in the neutralisation of ROS. It increases DNA methylation [ |
Riboflavin (vitamin B2) Pyridoxine (vitamin B6) Cobalamin (vitamin B12) | Cofactor involved in DNA methylation metabolism [ |
| Folate (vitamin B9) | It acts as a methyl donor involved in DNA methylation metabolism [ |
| It reduces the activity of DNA methyltransferase [ | |
| Choline | It acts as a methyl donor that can be recruited by human gut microbiota, reducing its availability [ |
| Involved in DNA methylation and gene expression in murine colitis model, an inflammatory disease [ | |
| Betaine | It acts as a methyl donor involved in DNA methylation reactions [ |
| Associated with changes in DNA methyltransferases and coupled with changes in DNA methylation [ | |
| Ammonium (NH4) | Inverse correlation between faecal NH3 and LINE-1 gene methylation [ |
| Involved in (de)methylation as a co-factor of histone demethylases and TET family [ | |
| L-ascorbic acid (vitamin C) | It exerts a strong influence on active DNA demethylation. It enhances TET-mediated generation of 5-hydroxymethylation [ |
ROS reactive oxygen species, NH ammonia, LINE-1 long interspersed element-1, TET ten–eleven translocation
Adapted from Mischke et al. [147]