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Cited by 640Epigenetics and DNA MethylationGenetic Syndromes and ImprintingGenomics and Chromatin Dynamics

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Principles of DNA methylation and their implications for biology and medicine

Dor, Yuval, Cedar, Howard·2018·The Lancet
DOI 10.1016/s0140-6736(18)31268-6
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Abstract

DNA methylation represents an annotation system for marking the genetic text, thus providing instruction as to how and when to read the information and control transcription. Unlike sequence information, which is inherited, methylation patterns are established in a programmed process that continues throughout development, thus setting up stable gene expression profiles. This DNA methylation paradigm is a key player in medicine. Some changes in methylation closely correlate with age providing a marker for biological ageing, and these same sites could also play a part in cancer. The genome continues to undergo programmed variation in methylation after birth in response to environmental inputs, serving as a memory device that could affect ageing and predisposition to various metabolic, autoimmune, and neurological diseases. Taking advantage of tissue-specific differences, methylation can be used to detect cell death and thereby monitor many common diseases with a simple cell-free circulating-DNA blood test.

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Research works printed but not linked: 81

  1. Bergman, 2013, DNA methylation dynamics in health and disease, Nat Struct Mol Biol, 20, 274, 10.1038/nsmb.2518 · DOI · Paper page
  2. Keshet, 1986, DNA methylation affects the formation of active chromatin, Cell, 44, 535, 10.1016/0092-8674(86)90263-1 · DOI
  3. Smith, 2014, DNA methylation dynamics of the human preimplantation embryo, Nature, 511, 611, 10.1038/nature13581 · DOI
  4. Smith, 2012, A unique regulatory phase of DNA methylation in the early mammalian embryo, Nature, 484, 339, 10.1038/nature10960 · DOI
  5. Cedar, 2012, Programming of DNA methylation patterns, Annu Rev Biochem, 81, 97, 10.1146/annurev-biochem-052610-091920 · DOI
  6. Straussman, 2009, Developmental programming of CpG island methylation profiles in the human genome, Nat Struct Mol Biol, 16, 564, 10.1038/nsmb.1594 · DOI
  7. Iurlaro, 2013, A screen for hydroxymethylcytosine and formylcytosine binding proteins suggests functions in transcription and chromatin regulation, Genome Biol, 14, R119, 10.1186/gb-2013-14-10-r119 · DOI
  8. Brocks, 2017, DNMT and HDAC inhibitors induce cryptic transcription start sites encoded in long terminal repeats, Nat Genet, 49, 1052, 10.1038/ng.3889 · DOI · Paper page
  9. Hon, 2013, Epigenetic memory at embryonic enhancers identified in DNA methylation maps from adult mouse tissues, Nat Genet, 45, 1198, 10.1038/ng.2746 · DOI
  10. Epsztejn-Litman, 2008, De novo DNA methylation promoted by G9a prevents reprogramming of embryonically silenced genes, Nat Struct Mol Biol, 15, 1176, 10.1038/nsmb.1476 · DOI
  11. Feldman, 2006, G9a-mediated irreversible epigenetic inactivation of Oct-3/4 during early embryogenesis, Nat Cell Biol, 8, 188, 10.1038/ncb1353 · DOI · Paper page
  12. Lu, 2014, Role of Tet proteins in enhancer activity and telomere elongation, Genes Dev, 28, 2103, 10.1101/gad.248005.114 · DOI
  13. Orlanski, 2016, Tissue-specific DNA demethylation is required for proper B-cell differentiation and function, Proc Natl Acad Sci USA, 113, 5018, 10.1073/pnas.1604365113 · DOI
  14. Klutstein, 2017, Contribution of epigenetic mechanisms to variation in cancer risk among tissues, Proc Natl Acad Sci USA, 114, 2230, 10.1073/pnas.1616556114 · DOI
  15. Horvath, 2014, Obesity accelerates epigenetic aging of human liver, Proc Natl Acad Sci USA, 111, 15538, 10.1073/pnas.1412759111 · DOI
  16. Maegawa, 2010, Widespread and tissue specific age-related DNA methylation changes in mice, Genome Res, 20, 332, 10.1101/gr.096826.109 · DOI · Paper page
  17. Nejman, 2013, Molecular rules governing de novo methylation in cancer, Cancer Res, 74, 1475, 10.1158/0008-5472.CAN-13-3042 · DOI
  18. Wang, 2017, Epigenetic aging signatures in mice livers are slowed by dwarfism, calorie restriction and rapamycin treatment, Genome Biol, 18, 57, 10.1186/s13059-017-1186-2 · DOI
  19. Maierhofer, 2017, Accelerated epigenetic aging in Werner syndrome, Aging (Albany NY), 9, 1143, 10.18632/aging.101217 · DOI
  20. Stubbs, 2017, Multi-tissue DNA methylation age predictor in mouse, Genome Biol, 18, 68, 10.1186/s13059-017-1203-5 · DOI · Paper page
  21. Armstrong, 2017, Aging, exceptional longevity and comparisons of the Hannum and Horvath epigenetic clocks, Epigenomics, 9, 689, 10.2217/epi-2016-0179 · DOI
  22. Jin, 2000, Understanding the molecular basis of fragile X syndrome, Hum Mol Genet, 9, 901, 10.1093/hmg/9.6.901 · DOI
  23. Elhamamsy, 2017, Role of DNA methylation in imprinting disorders: an updated review, J Assist Reprod Genet, 34, 549, 10.1007/s10815-017-0895-5 · DOI
  24. Horsthemke, 2014, In brief: genomic imprinting and imprinting diseases, J Pathol, 232, 485, 10.1002/path.4326 · DOI
  25. Liu, 2018, Rescue of fragile X syndrome neurons by DNA methylation editing of the FMR1 gene, Cell, 172, 979, 10.1016/j.cell.2018.01.012 · DOI
  26. Dover, 1983, 5-Azacytidine increases fetal hemoglobin production in a patient with sickle cell disease, Prog Clin Biol Res, 134, 475
  27. Ley, 1983, DNA methylation and globin gene expression in patients treated with 5-azacytidine, Prog Clin Biol Res, 134, 457
  28. Liao, 2017, In vivo target gene activation via CRISPR/Cas9-mediated trans-epigenetic modulation, Cell, 171, 1495, 10.1016/j.cell.2017.10.025 · DOI · Paper page
  29. Esteller, 2011, Epigenetic changes in cancer, F1000 Biol Rep, 3, 9, 10.3410/B3-9 · DOI
  30. Tomasetti, 2015, Cancer etiology. Variation in cancer risk among tissues can be explained by the number of stem cell divisions, Science, 347, 78, 10.1126/science.1260825 · DOI · Paper page
  31. Tomasetti, 2017, Role of stem-cell divisions in cancer risk, Nature, 548, E13, 10.1038/nature23302 · DOI
  32. Feinberg, 2006, The epigenetic progenitor origin of human cancer, Nat Rev Genet, 7, 21, 10.1038/nrg1748 · DOI
  33. Laird, 1995, Suppression of intestinal neoplasia by DNA hypomethylation, Cell, 81, 197, 10.1016/0092-8674(95)90329-1 · DOI
  34. Sun, 2014, Epigenomic profiling of young and aged HSCs reveals concerted changes during aging that reinforce self-renewal, Cell Stem Cell, 14, 673, 10.1016/j.stem.2014.03.002 · DOI · Paper page
  35. Raddatz, 2013, Aging is associated with highly defined epigenetic changes in the human epidermis, Epigenetics Chromatin, 6, 36, 10.1186/1756-8935-6-36 · DOI
  36. Feinberg, 2016, Epigenetic modulators, modifiers and mediators in cancer aetiology and progression, Nat Rev Genet, 17, 284, 10.1038/nrg.2016.13 · DOI · Paper page
  37. Abdel-Wahab, 2009, Genetic characterization of TET1, TET2, and TET3 alterations in myeloid malignancies, Blood, 114, 144, 10.1182/blood-2009-03-210039 · DOI · Paper page
  38. Aran, 2013, DNA methylation of transcriptional enhancers and cancer predisposition, Cell, 154, 11, 10.1016/j.cell.2013.06.018 · DOI
  39. Klutstein, 2016, DNA methylation in cancer and aging, Cancer Res, 76, 3446, 10.1158/0008-5472.CAN-15-3278 · DOI · Paper page
  40. Jones, 2016, Targeting the cancer epigenome for therapy, Nat Rev Genet, 17, 630, 10.1038/nrg.2016.93 · DOI
  41. Chiappinelli, 2016, Combining epigenetic and immunotherapy to combat cancer, Cancer Res, 76, 1683, 10.1158/0008-5472.CAN-15-2125 · DOI
  42. Ghoneim, 2017, De novo epigenetic programs inhibit PD-1 blockade-mediated T cell rejuvenation, Cell, 170, 142, 10.1016/j.cell.2017.06.007 · DOI
  43. Dabelea, 2000, Effect of diabetes in pregnancy on offspring: follow-up research in the Pima Indians, J Matern Fetal Med, 9, 83
  44. Tobi, 2014, DNA methylation signatures link prenatal famine exposure to growth and metabolism, Nat Commun, 5, 5592, 10.1038/ncomms6592 · DOI · Paper page
  45. Tulisiak, 2017, DNA modifications in models of alcohol use disorders, Alcohol, 60, 19, 10.1016/j.alcohol.2016.11.004 · DOI
  46. Weaver, 2004, Epigenetic programming by maternal behavior, Nat Neurosci, 7, 847, 10.1038/nn1276 · DOI · Paper page
  47. Abu-Remaileh, 2015, Chronic inflammation induces a novel epigenetic program that is conserved in intestinal adenomas and in colorectal cancer, Cancer Res, 75, 2120, 10.1158/0008-5472.CAN-14-3295 · DOI
  48. Hodjat, 2017, Environmental toxicants, incidence of degenerative diseases, and therapies from the epigenetic point of view, Arch Toxicol, 91, 2577, 10.1007/s00204-017-1979-9 · DOI
  49. Lappalainen, 2017, Associating cellular epigenetic models with human phenotypes, Nat Rev Genet, 18, 441, 10.1038/nrg.2017.32 · DOI · Paper page
  50. van Dijk, 2015, Recent developments on the role of epigenetics in obesity and metabolic disease, Clin Epigenetics, 7, 66, 10.1186/s13148-015-0101-5 · DOI
  51. Roth, 2009, Epigenetic mechanisms in schizophrenia, Biochim Biophys Acta, 1790, 869, 10.1016/j.bbagen.2009.06.009 · DOI
  52. Montano, 2016, Association of DNA methylation differences with schizophrenia in an epigenome-wide association study, JAMA Psychiatry, 73, 506, 10.1001/jamapsychiatry.2016.0144 · DOI · Paper page
  53. Multhaup, 2015, Mouse-human experimental epigenetic analysis unmasks dietary targets and genetic liability for diabetic phenotypes, Cell Metab, 21, 138, 10.1016/j.cmet.2014.12.014 · DOI
  54. Long, 2016, The critical role of epigenetics in systemic lupus erythematosus and autoimmunity, J Autoimmun, 74, 118, 10.1016/j.jaut.2016.06.020 · DOI
  55. Zhao, 2016, IFI44L promoter methylation as a blood biomarker for systemic lupus erythematosus, Ann Rheum Dis, 75, 1998, 10.1136/annrheumdis-2015-208410 · DOI
  56. Gilsbach, 2014, Dynamic DNA methylation orchestrates cardiomyocyte development, maturation and disease, Nat Commun, 5, 5288, 10.1038/ncomms6288 · DOI
  57. Dos Santos, 2015, An epigenetic memory of pregnancy in the mouse mammary gland, Cell Rep, 11, 1102, 10.1016/j.celrep.2015.04.015 · DOI
  58. Cannon, 2016, Extensive epigenetic changes accompany terminal differentiation of mouse hepatocytes after birth, G3 (Bethesda), 6, 3701, 10.1534/g3.116.034785 · DOI
  59. Ehara, 2015, Ligand-activated PPARalpha-dependent DNA demethylation regulates the fatty acid beta-oxidation genes in the postnatal liver, Diabetes, 64, 775, 10.2337/db14-0158 · DOI
  60. Reizel, 2018, Postnatal DNA demethylation and its role in tissue maturation, Nat Commun, 9, 2040, 10.1038/s41467-018-04456-6 · DOI · Paper page
  61. Reizel, 2015, Gender-specific postnatal demethylation and establishment of epigenetic memory, Genes Dev, 29, 923, 10.1101/gad.259309.115 · DOI
  62. Jiang, 2016, The long and short of circulating cell-free DNA and the ins and outs of molecular diagnostics, Trends Genet, 32, 360, 10.1016/j.tig.2016.03.009 · DOI
  63. Fan, 2012, Non-invasive prenatal measurement of the fetal genome, Nature, 487, 320, 10.1038/nature11251 · DOI
  64. Lo, 1997, Presence of fetal DNA in maternal plasma and serum, Lancet, 350, 485, 10.1016/S0140-6736(97)02174-0 · DOI · Paper page
  65. Abbosh, 2017, Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution, Nature, 545, 446, 10.1038/nature22364 · DOI
  66. Crowley, 2013, Liquid biopsy: monitoring cancer-genetics in the blood, Nat Rev Clin Oncol, 10, 472, 10.1038/nrclinonc.2013.110 · DOI
  67. Snyder, 2011, Universal non-invasive detection of solid organ transplant rejection, Proc Natl Acad Sci USA, 108, 6229, 10.1073/pnas.1013924108 · DOI
  68. Akirav, 2011, Detection of beta cell death in diabetes using differentially methylated circulating DNA, Proc Natl Acad Sci USA, 108, 19018, 10.1073/pnas.1111008108 · DOI
  69. Lehmann-Werman, 2016, Identification of tissue-specific cell death using methylation patterns of circulating DNA, Proc Natl Acad Sci USA, 113, E1826, 10.1073/pnas.1519286113 · DOI
  70. Sun, 2015, Plasma DNA tissue mapping by genome-wide methylation sequencing for non-invasive prenatal, cancer, and transplantation assessments, Proc Natl Acad Sci USA, 112, E5503, 10.1073/pnas.1508736112 · DOI
  71. Zemmour, 2018, Non-invasive detection of human cardiomyocyte death using methylation patterns of circulating DNA, Nat Commun, 9, 1443, 10.1038/s41467-018-03961-y · DOI
  72. Gala-Lopez, 2018, Beta cell death by cell-free DNA and outcome after clinical islet transplantation, Transplantation, 102, 978, 10.1097/TP.0000000000002083 · DOI
  73. Bellin, 2017, Unmethylated insulin DNA is elevated after total pancreatectomy with islet autotransplantation: assessment of a novel beta cell marker, Am J Transplant, 17, 1112, 10.1111/ajt.14054 · DOI
  74. Moran, 2017, Precision medicine based on epigenomics: the paradigm of carcinoma of unknown primary, Nat Rev Clin Oncol, 14, 682, 10.1038/nrclinonc.2017.97 · DOI
  75. Moran, 2016, Epigenetic profiling to classify cancer of unknown primary: a multicentre, retrospective analysis, Lancet Oncol, 17, 1386, 10.1016/S1470-2045(16)30297-2 · DOI
  76. Hao, 2017, DNA methylation markers for diagnosis and prognosis of common cancers, Proc Natl Acad Sci USA, 114, 7414, 10.1073/pnas.1703577114 · DOI
  77. Guo, 2017, Identification of methylation haplotype blocks aids in deconvolution of heterogeneous tissue samples and tumor tissue-of-origin mapping from plasma DNA, Nat Genet, 49, 635, 10.1038/ng.3805 · DOI
  78. Kang, 2017, CancerLocator: non-invasive cancer diagnosis and tissue-of-origin prediction using methylation profiles of cell-free DNA, Genome Biol, 18, 53, 10.1186/s13059-017-1191-5 · DOI
  79. Daxinger, 2012, Understanding transgenerational epigenetic inheritance via the gametes in mammals, Nat Rev Genet, 13, 153, 10.1038/nrg3188 · DOI
  80. Bohacek, 2015, Molecular insights into transgenerational non-genetic inheritance of acquired behaviours, Nat Rev Genet, 16, 641, 10.1038/nrg3964 · DOI · Paper page
  81. Pulecio, 2017, CRISPR/Cas9-based engineering of the epigenome, Cell Stem Cell, 21, 431, 10.1016/j.stem.2017.09.006 · DOI · Paper page

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Metadata

Authors
Dor, Y., & Cedar, H.
Affiliations
Hebrew University of Jerusalem (IL)
Corresponding author
Cedar, Howard
ORCID
Venue
The Lancet
Publisher
Elsevier BV
Published
2018-09
Volume
392
Issue
10149
Pages
777-786
ISSN
  • 0099-5355 (ISSN-L)
  • 0140-6736
DOI
10.1016/s0140-6736(18)31268-6
OpenAlex
W2886223143
Cited by
640
References
19
Citations by year
2026: 54 · 2025: 79 · 2024: 76 · 2023: 82 · 2022: 111 · 2021: 102 · 2020: 75 · 2019: 53 · 2018: 7
FWCI
5.81
Type
journal article
Language
en
Open access
closed
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations
  • The Lancet (publishedVersion)
  • PubMed (publishedVersion)
Funders
Rosetrees Trust (M31-F2)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Syndromes and Imprinting
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
Keywords
DNA methylation, epigenetics, gene expression regulation, biological aging, cancer, disease susceptibility, cell-free DNA, liquid biopsy, cell death detection, tissue-specific methylation
MeSH terms
Cell-Free Nucleic Acids, Aging, Diagnosis, Humans, Neoplasms, Biomarkers, DNA Methylation, Epigenesis, Genetic, Gene-Environment Interaction

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