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Epigenetics and Type 2 Diabetes Risk

  • Pathogenesis of Type 2 Diabetes and Insulin Resistance (M-E Patti, Section Editor)
  • Published:
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Abstract

Purpose of Review

The influence of environmental factors on type 2 diabetes (T2D) risk is now well recognized and highlights the contribution of epigenetic mechanisms. This review will focus on the role of epigenetic factors in the risk and pathogenesis of T2D.

Recent Findings

Epigenetic dysregulation has emerged as a key mechanism underpinning the pathogenesis of T2D and its complications. Environmental variations, including alterations in lifestyle, nutrition, and metabolic demands during prenatal and postnatal life can induce epigenetic changes that may impact glucose homeostasis and the function of different metabolic organs. Accumulating data continues to uncover the specific pathways that are epigenetically dysregulated in T2D, providing an opportunity for therapeutic targeting.

Summary

Environmental changes can disrupt specific epigenetic mechanisms underlying metabolic homeostasis, thus contributing to T2D pathogenesis. Such epigenetic changes can be transmitted to the next generation, contributing to the inheritance of T2D risk. Recent advances in epigenome-wide association studies and epigenetic editing tools present the attractive possibility of identifying epimutations associated with T2D, correcting specific epigenetic alterations, and designing novel epigenetic biomarkers and interventions for T2D.

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References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. Zimmet PZ, Magliano DJ, Herman WH, Shaw JE. Diabetes: a 21st century challenge. Lancet Diabetes Endocrinol. 2014;2(1):56–64. https://doi.org/10.1016/S2213-8587(13)70112-8.

    Article  PubMed  Google Scholar 

  2. Forbes JM, Cooper ME. Mechanisms of diabetic complications. Physiol Rev. 2013;93(1):137–88. https://doi.org/10.1152/physrev.00045.2011.

    Article  CAS  PubMed  Google Scholar 

  3. Reddy MA, Zhang E, Natarajan R. Epigenetic mechanisms in diabetic complications and metabolic memory. Diabetologia. 2015;58(3):443–55. https://doi.org/10.1007/s00125-014-3462-y.

    Article  CAS  PubMed  Google Scholar 

  4. Almgren P, Lehtovirta M, Isomaa B, Sarelin L, Taskinen MR, Lyssenko V, et al. Heritability and familiality of type 2 diabetes and related quantitative traits in the Botnia Study. Diabetologia. 2011;54(11):2811–9. https://doi.org/10.1007/s00125-011-2267-5.

    Article  CAS  PubMed  Google Scholar 

  5. Meigs JB, Cupples LA, Wilson PW. Parental transmission of type 2 diabetes: the Framingham Offspring Study. Diabetes. 2000;49(12):2201–7.

    Article  CAS  PubMed  Google Scholar 

  6. • Fuchsberger C, Flannick J, Teslovich TM, Mahajan A, Agarwala V, Gaulton KJ, et al. The genetic architecture of type 2 diabetes. Nature. 2016;536(7614):41–7. https://doi.org/10.1038/nature18642. This study provides a comprehensive analysis of the contribution of genetic factors to T2D risk.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Manolio TA, Collins FS, Cox NJ, Goldstein DB, Hindorff LA, Hunter DJ, et al. Finding the missing heritability of complex diseases. Nature. 2009;461(7265):747–53. https://doi.org/10.1038/nature08494.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. • Ahlqvist E, Storm P, Karajamaki A, Martinell M, Dorkhan M, Carlsson A et al. Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables. Lancet Diabetes Endocrinol 2018;6(5):361–369. doi:https://doi.org/10.1016/S2213-8587(18)30051-2. This study highlights the heterogeneity and complexity of adult-onset diabetes.

    Article  Google Scholar 

  9. Unnikrishnan R, Pradeepa R, Joshi SR, Mohan V. Type 2 diabetes: demystifying the global epidemic. Diabetes. 2017;66(6):1432–42. https://doi.org/10.2337/db16-0766.

    Article  CAS  PubMed  Google Scholar 

  10. Rosen ED, Kaestner KH, Natarajan R, Patti ME, Sallari R, Sander M, et al. Epigenetics and epigenomics: implications for diabetes and obesity. Diabetes. 2018;67(10):1923–31. https://doi.org/10.2337/db18-0537.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Ling C, Groop L. Epigenetics: a molecular link between environmental factors and type 2 diabetes. Diabetes. 2009;58(12):2718–25. https://doi.org/10.2337/db09-1003.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Allis CD, Jenuwein T. The molecular hallmarks of epigenetic control. Nat Rev Genet. 2016;17(8):487–500. https://doi.org/10.1038/nrg.2016.59.

    Article  CAS  PubMed  Google Scholar 

  13. Sassone-Corsi P. Physiology. When metabolism and epigenetics converge. Science. 2013;339(6116):148–50. https://doi.org/10.1126/science.

    Article  CAS  PubMed  Google Scholar 

  14. Arnes L, Sussel L. Epigenetic modifications and long noncoding RNAs influence pancreas development and function. Trends Genet. 2015;31(6):290–9. https://doi.org/10.1016/j.tig.2015.02.008S0168-9525(15)00036-0.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Bansal A, Simmons RA. Epigenetics and developmental origins of diabetes: correlation or causation? Am J Physiol Endocrinol Metab. 2018;315(1):E15–28. https://doi.org/10.1152/ajpendo.00424.2017.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Heijmans BT, Tobi EW, Stein AD, Putter H, Blauw GJ, Susser ES, et al. Persistent epigenetic differences associated with prenatal exposure to famine in humans. Proc Natl Acad Sci U S A. 2008;105(44):17046–9. https://doi.org/10.1073/pnas.0806560105.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Hales CN, Barker DJ. The thrifty phenotype hypothesis. Br Med Bull. 2001;60:5–20.

    Article  CAS  PubMed  Google Scholar 

  18. Carone BR, Fauquier L, Habib N, Shea JM, Hart CE, Li R, et al. Paternally induced transgenerational environmental reprogramming of metabolic gene expression in mammals. Cell. 2010;143(7):1084–96. https://doi.org/10.1016/j.cell.2010.12.008.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Ng SF, Lin RC, Laybutt DR, Barres R, Owens JA, Morris MJ. Chronic high-fat diet in fathers programs beta-cell dysfunction in female rat offspring. Nature. 2010;467(7318):963–6. https://doi.org/10.1038/nature09491.

    Article  CAS  PubMed  Google Scholar 

  20. Sales VM, Ferguson-Smith AC, Patti ME. Epigenetic mechanisms of transmission of metabolic disease across generations. Cell Metab. 2017;25(3):559–71. https://doi.org/10.1016/j.cmet.2017.02.016.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Martinez D, Pentinat T, Ribo S, Daviaud C, Bloks VW, Cebria J, et al. In utero undernutrition in male mice programs liver lipid metabolism in the second-generation offspring involving altered Lxra DNA methylation. Cell Metab. 2014;19(6):941–51. https://doi.org/10.1016/j.cmet.2014.03.026.

    Article  CAS  PubMed  Google Scholar 

  22. de Castro Barbosa T, Ingerslev LR, Alm PS, Versteyhe S, Massart J, Rasmussen M, et al. High-fat diet reprograms the epigenome of rat spermatozoa and transgenerationally affects metabolism of the offspring. Mol Metab. 2016;5(3):184–97. https://doi.org/10.1016/j.molmet.2015.12.002.

    Article  CAS  PubMed  Google Scholar 

  23. •• Donkin I, Versteyhe S, Ingerslev LR, Qian K, Mechta M, Nordkap L, et al. Obesity and Bariatric Surgery Drive Epigenetic Variation of Spermatozoa in Humans. Cell Metab. 2016;23(2):369–78. https://doi.org/10.1016/j.cmet.2015.11.004. This study demonstrates that variations in the body mass index can reprogram the epigenome of spermatozoa, providing novel insights into the inheritance of metabolic disease risk.

    Article  CAS  PubMed  Google Scholar 

  24. Kong A, Steinthorsdottir V, Masson G, Thorleifsson G, Sulem P, Besenbacher S, et al. Parental origin of sequence variants associated with complex diseases. Nature. 2009;462(7275):868–74. https://doi.org/10.1038/nature08625nature08625.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Xu CR, Cole PA, Meyers DJ, Kormish J, Dent S, Zaret KS. Chromatin “prepattern” and histone modifiers in a fate choice for liver and pancreas. Science. 2011;332(6032):963–6. https://doi.org/10.1126/science.1202845.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. McKenna B, Guo M, Reynolds A, Hara M, Stein R. Dynamic recruitment of functionally distinct Swi/Snf chromatin remodeling complexes modulates Pdx1 activity in islet beta cells. Cell Rep. 2015;10(12):2032–42. https://doi.org/10.1016/j.celrep.2015.02.054.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Georgia S, Kanji M, Bhushan A. DNMT1 represses p53 to maintain progenitor cell survival during pancreatic organogenesis. Genes Dev. 2013;27(4):372–7. https://doi.org/10.1101/gad.207001.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Lenoir O, Flosseau K, Ma FX, Blondeau B, Mai A, Bassel-Duby R, et al. Specific control of pancreatic endocrine beta- and delta-cell mass by class IIa histone deacetylases HDAC4, HDAC5. and HDAC9. Diabetes. 2011;60(11):2861–71. https://doi.org/10.2337/db11-0440db11-0440.

    Article  CAS  PubMed  Google Scholar 

  29. Wang A, Yue F, Li Y, Xie R, Harper T, Patel NA, et al. Epigenetic priming of enhancers predicts developmental competence of hESC-derived endodermal lineage intermediates. Cell Stem Cell. 2015;16(4):386–99. https://doi.org/10.1016/j.stem.2015.02.013.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Papizan JB, Singer RA, Tschen SI, Dhawan S, Friel JM, Hipkens SB, et al. Nkx2.2 repressor complex regulates islet beta-cell specification and prevents beta-to-alpha-cell reprogramming. Genes Dev. 2011;25(21):2291–305. https://doi.org/10.1101/gad.173039.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Dhawan S, Georgia S, Tschen SI, Fan G, Bhushan A. Pancreatic beta cell identity is maintained by DNA methylation-mediated repression of Arx. Dev Cell. 2011;20(4):419–29. https://doi.org/10.1016/j.devcel.2011.03.012S1534-5807(11)00118-3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Dhawan S, Tschen SI, Zeng C, Guo T, Hebrok M, Matveyenko A, et al. DNA methylation directs functional maturation of pancreatic beta cells. J Clin Invest. 2015;125(7):2851–60. https://doi.org/10.1172/JCI7995679956.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Neiman D, Moss J, Hecht M, Magenheim J, Piyanzin S, Shapiro AMJ, et al. Islet cells share promoter hypomethylation independently of expression, but exhibit cell-type-specific methylation in enhancers. Proc Natl Acad Sci U S A. 2017;114(51):13525–30. https://doi.org/10.1073/pnas.1713736114.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Martinez-Sanchez A, Rutter GA, Latreille M. MiRNAs in beta-cell development, identity, and disease. Front Genet. 2016;7:226. https://doi.org/10.3389/fgene.2016.00226.

    Article  CAS  PubMed  Google Scholar 

  35. Singer RA, Sussel L. Islet long noncoding RNAs: a playbook for discovery and characterization. Diabetes. 2018;67(8):1461–70. https://doi.org/10.2337/dbi18-0001.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. LaPierre MP, Stoffel M. MicroRNAs as stress regulators in pancreatic beta cells and diabetes. Mol Metab. 2017;6(9):1010–23. https://doi.org/10.1016/j.molmet.2017.06.020.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Kanji MS, Martin MG, Bhushan A. Dicer1 is required to repress neuronal fate during endocrine cell maturation. Diabetes. 2013;62(5):1602–11. https://doi.org/10.2337/db12-0841.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Lynn FC, Skewes-Cox P, Kosaka Y, McManus MT, Harfe BD, German MS. MicroRNA expression is required for pancreatic islet cell genesis in the mouse. Diabetes. 2007;56(12):2938–45. https://doi.org/10.2337/db07-0175.

    Article  CAS  PubMed  Google Scholar 

  39. Jacovetti C, Matkovich SJ, Rodriguez-Trejo A, Guay C, Regazzi R. Postnatal beta-cell maturation is associated with islet-specific microRNA changes induced by nutrient shifts at weaning. Nat Commun. 2015;6:8084. https://doi.org/10.1038/ncomms9084.

    Article  PubMed  Google Scholar 

  40. •• Arnes L, Akerman I, Balderes DA, Ferrer J, Sussel L. betalinc1 encodes a long noncoding RNA that regulates islet beta-cell formation and function. Genes Dev. 2016;30(5):502–7. https://doi.org/10.1101/gad.273821.115. This study discovered a novel role for lncRNAs in the regulation of beta cell homeostasis.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Karnik SK, Hughes CM, Gu X, Rozenblatt-Rosen O, McLean GW, Xiong Y, et al. Menin regulates pancreatic islet growth by promoting histone methylation and expression of genes encoding p27Kip1 and p18INK4c. Proc Natl Acad Sci U S A. 2005;102(41):14659–64. https://doi.org/10.1073/pnas.0503484102.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Dhawan S, Tschen SI, Bhushan A. Bmi-1 regulates the Ink4a/Arf locus to control pancreatic beta-cell proliferation. Genes Dev. 2009;23(8):906–11. https://doi.org/10.1101/gad.1742609.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Chen H, Gu X, Su IH, Bottino R, Contreras JL, Tarakhovsky A, et al. Polycomb protein Ezh2 regulates pancreatic beta-cell Ink4a/Arf expression and regeneration in diabetes mellitus. Genes Dev. 2009;23(8):975–85. https://doi.org/10.1101/gad.174250923/8/975.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. • Sanchez-Parra C, Jacovetti C, Dumortier O, Lee K, Peyot ML, Guay C, et al. Contribution of the long noncoding RNA H19 to beta-cell mass expansion in neonatal and adult rodents. Diabetes. 2018;67(11):2254–67. https://doi.org/10.2337/db18-0201. This study identified a role for combinatorial epigenetic regulation via genomic imprinting and lncRNAs in beta cell homeostasis.

    Article  CAS  PubMed  Google Scholar 

  45. Chen H, Gu X, Liu Y, Wang J, Wirt SE, Bottino R, et al. PDGF signalling controls age-dependent proliferation in pancreatic beta-cells. Nature. 2011;478(7369):349–55. https://doi.org/10.1038/nature10502nature10502.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. • Dhawan S, Dirice E, Kulkarni RN, Bhushan A. Inhibition of TGF-beta signaling promotes human pancreatic beta cell replication. Diabetes. 2016;151331:15–1331. https://doi.org/10.2337/db15-1331. This study highlights how cellular signals regulate beta cell replication via epiegentic remodeling of cell-cycle machinery, with implications for therapeutic targeting.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Avrahami D, Li C, Zhang J, Schug J, Avrahami R, Rao S, et al. Aging-dependent demethylation of regulatory elements correlates with chromatin state and improved beta cell function. Cell Metab. 2015;22(4):619–32. https://doi.org/10.1016/j.cmet.2015.07.025.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Golson ML, Kaestner KH. Epigenetics in formation, function, and failure of the endocrine pancreas. Mol Metab. 2017;6(9):1066–76. https://doi.org/10.1016/j.molmet.2017.05.015.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Prokopenko I, Poon W, Magi R, Prasad BR, Salehi SA, Almgren P, et al. A central role for GRB10 in regulation of islet function in man. PLoS Genet. 2014;10(4):e1004235. https://doi.org/10.1371/journal.pgen.1004235.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Travers ME, Mackay DJ, Dekker Nitert M, Morris AP, Lindgren CM, Berry A, et al. Insights into the molecular mechanism for type 2 diabetes susceptibility at the KCNQ1 locus from temporal changes in imprinting status in human islets. Diabetes. 2013;62(3):987–92. https://doi.org/10.2337/db12-0819.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Dayeh T, Volkov P, Salo S, Hall E, Nilsson E, Olsson AH, et al. Genome-wide DNA methylation analysis of human pancreatic islets from type 2 diabetic and non-diabetic donors identifies candidate genes that influence insulin secretion. PLoS Genet. 2014;10(3):e1004160. https://doi.org/10.1371/journal.pgen.1004160PGENETICS-D-13-01899.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Kameswaran V, Bramswig NC, McKenna LB, Penn M, Schug J, Hand NJ, et al. Epigenetic regulation of the DLK1-MEG3 microRNA cluster in human type 2 diabetic islets. Cell Metab. 2014;19(1):135–45. https://doi.org/10.1016/j.cmet.2013.11.016.

    Article  CAS  PubMed  Google Scholar 

  53. • Rodnoi P, Rajkumar M, Moin ASM, Georgia SK, Butler AE, Dhawan S. Neuropeptide Y expression marks partially differentiated beta cells in mice and humans. JCI Insight. 2017;2(12). https://doi.org/10.1172/jci.insight.94005. The data presented in this study point to epigenetic dysregulation as a key mechanism contrbuting to beta cell de-differentiation and dysfunction in T2D.

  54. Talchai C, Xuan S, Lin HV, Sussel L, Accili D. Pancreatic beta cell dedifferentiation as a mechanism of diabetic beta cell failure. Cell. 2012;150(6):1223–34. https://doi.org/10.1016/j.cell.2012.07.029S0092-8674(12)00940-3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. •• Lu TT, Heyne S, Dror E, Casas E, Leonhardt L, Boenke T, et al. The Polycomb-Dependent Epigenome Controls beta Cell Dysfunction, Dedifferentiation, and Diabetes. Cell Metab. 2018;27(6):1294–308 e7. https://doi.org/10.1016/j.cmet.2018.04.013. This study uncovered a novel regulatory role for polycomb protein Eed in beta cell identity and function, and showed that polycomb disruption leads to beta cell de-differentiation and dysfunction in T2D.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Zhang H, Pollin TI. Epigenetics variation and pathogenesis in diabetes. Curr Diab Rep. 2018;18(11):121. https://doi.org/10.1007/s11892-018-1091-4.

    Article  PubMed  Google Scholar 

  57. Dirks RA, Stunnenberg HG, Marks H. Genome-wide epigenomic profiling for biomarker discovery. Clin Epigenetics. 2016;8:122. https://doi.org/10.1186/s13148-016-0284-4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Goodwin S, McPherson JD, McCombie WR. Coming of age: ten years of next-generation sequencing technologies. Nat Rev Genet. 2016;17(6):333–51. https://doi.org/10.1038/nrg.2016.49.

    Article  CAS  PubMed  Google Scholar 

  59. Volkmar M, Dedeurwaerder S, Cunha DA, Ndlovu MN, Defrance M, Deplus R, et al. DNA methylation profiling identifies epigenetic dysregulation in pancreatic islets from type 2 diabetic patients. EMBO J. 2012;31(6):1405–26. https://doi.org/10.1038/emboj.2011.503.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. • Volkov P, Bacos K, Ofori JK, Esguerra JL, Eliasson L, Ronn T, et al. Whole-Genome Bisulfite Sequencing of Human Pancreatic Islets Reveals Novel Differentially Methylated Regions in Type 2 Diabetes Pathogenesis. Diabetes. 2017;66(4):1074–85. https://doi.org/10.2337/db16-0996. The data presented in this article point to large-scale epigenetic dysregulation in pancreatic islets in the context of T2D, and provide mechanistic insights into how such epigenetic changes may alter islet function.

    Article  CAS  PubMed  Google Scholar 

  61. Feinberg AP, Irizarry RA, Fradin D, Aryee MJ, Murakami P, Aspelund T, et al. Personalized epigenomic signatures that are stable over time and covary with body mass index. Sci Transl Med. 2010;2(49):49ra67. https://doi.org/10.1126/scitranslmed.3001262.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Walaszczyk E, Luijten M, Spijkerman AMW, Bonder MJ, Lutgers HL, Snieder H, et al. DNA methylation markers associated with type 2 diabetes, fasting glucose and HbA1c levels: a systematic review and replication in a case-control sample of the Lifelines study. Diabetologia. 2018;61(2):354–68. https://doi.org/10.1007/s00125-017-4497-7.

    Article  CAS  PubMed  Google Scholar 

  63. Nilsson E, Jansson PA, Perfilyev A, Volkov P, Pedersen M, Svensson MK, et al. Altered DNA methylation and differential expression of genes influencing metabolism and inflammation in adipose tissue from subjects with type 2 diabetes. Diabetes. 2014;63(9):2962–76. https://doi.org/10.2337/db13-1459.

    Article  PubMed  Google Scholar 

  64. Crujeiras AB, Diaz-Lagares A, Moreno-Navarrete JM, Sandoval J, Hervas D, Gomez A, et al. Genome-wide DNA methylation pattern in visceral adipose tissue differentiates insulin-resistant from insulin-sensitive obese subjects. Transl Res. 2016;178:13–24 e5. https://doi.org/10.1016/j.trsl.2016.07.002.

    Article  CAS  PubMed  Google Scholar 

  65. •• Wahl S, Drong A, Lehne B, Loh M, Scott WR, Kunze S, et al. Epigenome-wide association study of body mass index, and the adverse outcomes of adiposity. Nature. 2017;541(7635):81–6. https://doi.org/10.1038/nature20784. The data presented in this study provide a novel insight into the specific physiological pathways that are epigenetically dysregulated by adiposity.

    Article  PubMed  PubMed Central  Google Scholar 

  66. Multhaup ML, Seldin MM, Jaffe AE, Lei X, Kirchner H, Mondal P, et al. Mouse-human experimental epigenetic analysis unmasks dietary targets and genetic liability for diabetic phenotypes. Cell Metab. 2015;21(1):138–49. https://doi.org/10.1016/j.cmet.2014.12.014.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Nitert MD, Dayeh T, Volkov P, Elgzyri T, Hall E, Nilsson E, et al. Impact of an exercise intervention on DNA methylation in skeletal muscle from first-degree relatives of patients with type 2 diabetes. Diabetes. 2012;61(12):3322–32. https://doi.org/10.2337/db11-1653.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. • Scott LJ, Erdos MR, Huyghe JR, Welch RP, Beck AT, Wolford BN, et al. The genetic regulatory signature of type 2 diabetes in human skeletal muscle. Nat Commun. 2016;7:11764. https://doi.org/10.1038/ncomms11764. This study illustrates the power of combining genome- and epigenome-wide association data to identify the molecular underpinnings of type 2 diabetes pathogenesis.

  69. Kirchner H, Sinha I, Gao H, Ruby MA, Schonke M, Lindvall JM, et al. Altered DNA methylation of glycolytic and lipogenic genes in liver from obese and type 2 diabetic patients. Mol Metab. 2016;5(3):171–83. https://doi.org/10.1016/j.molmet.2015.12.004.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Jacobsen SC, Gillberg L, Bork-Jensen J, Ribel-Madsen R, Lara E, Calvanese V, et al. Young men with low birthweight exhibit decreased plasticity of genome-wide muscle DNA methylation by high-fat overfeeding. Diabetologia. 2014;57(6):1154–8. https://doi.org/10.1007/s00125-014-3198-8.

    Article  CAS  PubMed  Google Scholar 

  71. Gillberg L, Perfilyev A, Brons C, Thomasen M, Grunnet LG, Volkov P, et al. Adipose tissue transcriptomics and epigenomics in low birthweight men and controls: role of high-fat overfeeding. Diabetologia. 2016;59(4):799–812. https://doi.org/10.1007/s00125-015-3852-9.

    Article  CAS  PubMed  Google Scholar 

  72. Barres R, Yan J, Egan B, Treebak JT, Rasmussen M, Fritz T, et al. Acute exercise remodels promoter methylation in human skeletal muscle. Cell Metab. 2012;15(3):405–11. https://doi.org/10.1016/j.cmet.2012.01.001.

    Article  CAS  PubMed  Google Scholar 

  73. • Fabre O, Ingerslev LR, Garde C, Donkin I, Simar D, Barres R. Exercise training alters the genomic response to acute exercise in human adipose tissue. Epigenomics. 2018;10(8):1033–50. https://doi.org/10.2217/epi-2018-0039. This study demonstrates that the human sWAT epigenome is sensitive to acute exercise regimen.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Thompson RF, Fazzari MJ, Niu H, Barzilai N, Simmons RA, Greally JM. Experimental intrauterine growth restriction induces alterations in DNA methylation and gene expression in pancreatic islets of rats. J Biol Chem. 2010;285(20):15111–8. https://doi.org/10.1074/jbc.M109.095133.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Samuel VT, Shulman GI. The pathogenesis of insulin resistance: integrating signaling pathways and substrate flux. J Clin Invest. 2016;126(1):12–22. https://doi.org/10.1172/JCI77812.

    Article  PubMed  PubMed Central  Google Scholar 

  76. You D, Nilsson E, Tenen DE, Lyubetskaya A, Lo JC, Jiang R, et al. Dnmt3a is an epigenetic mediator of adipose insulin resistance. Elife. 2017;6. https://doi.org/10.7554/eLife.30766.

  77. Kang S, Tsai LT, Zhou Y, Evertts A, Xu S, Griffin MJ, et al. Identification of nuclear hormone receptor pathways causing insulin resistance by transcriptional and epigenomic analysis. Nat Cell Biol. 2015;17(1):44–56. https://doi.org/10.1038/ncb3080.

    Article  CAS  PubMed  Google Scholar 

  78. • Alm PS, de Castro Barbosa T, Barres R, Krook A, Zierath JR. Grandpaternal-induced transgenerational dietary reprogramming of the unfolded protein response in skeletal muscle. Mol Metab. 2017;6(7):621–30. https://doi.org/10.1016/j.molmet.2017.05.009. This study highlights how adverse environmental factors impact diabetes risk through generations.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. •• Roh HC, Tsai LTY, Shao M, Tenen D, Shen Y, Kumari M, Lyubetskaya A, Jacobs C, Dawes B, Gupta RK, Rosen ED Warming induces significant reprogramming of beige, but not brown, adipocyte cellular identity Cell Metab 2018;27(5):1121–37 e5. doi:https://doi.org/10.1016/j.cmet.2018.03.005. This study identified the epigenetic basis of adipose cellular plasticity in response to changes in ambient temperature.

    Article  PubMed  PubMed Central  Google Scholar 

  80. •• Sun W, Dong H, Becker AS, Dapito DH, Modica S, Grandl G, et al. Cold-induced epigenetic programming of the sperm enhances brown adipose tissue activity in the offspring. Nat Med. 2018;24(9):1372–83. https://doi.org/10.1038/s41591-018-0102-y. This study illustrates how seasonal variations in temperature can reprogram the sperm epigenome to confer adaptive advantage to the offspring.

    Article  CAS  PubMed  Google Scholar 

  81. Sassone-Corsi P. The epigenetic and metabolic language of the circadian clock. In: Sassone-Corsi P, Christen Y, editors. A time for metabolism and hormones. Cham (CH)2016. p. 1–11.

    Google Scholar 

  82. •• Benegiamo G, Mure LS, Erikson G, Le HD, Moriggi E, Brown SA et al. The RNA-Binding Protein NONO Coordinates Hepatic Adaptation to Feeding. Cell Metab. 2018;27(2):404–18 e7. https://doi.org/10.1016/j.cmet.2017.12.010. This study identified NONO as a key lncRNA species that regulates hepatic metabolism in response to feeding behavior.

    Article  PubMed  PubMed Central  Google Scholar 

  83. Colwell CS, Matveyenko AV. Timing is everything: implications for metabolic consequences of sleep restriction. Diabetes. 2014;63(6):1826–8. https://doi.org/10.2337/db14-0283.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. •• Chaix A, Lin T, Le HD, Chang MW, Panda S. Time-restricted feeding prevents obesity and metabolic syndrome in mice lacking a circadian clock. Cell Metab. 2018;29:303–319.e4. https://doi.org/10.1016/j.cmet.2018.08.004. This study highlights how the mechanistic link between feeding-fasting and circadian clock serves to maintain homeostasis, and points to a protective effect of time-restricted feeding on metabolic health.

    Article  PubMed  Google Scholar 

  85. Zimmet P, Shi Z, El-Osta A, Ji L. Epidemic T2DM, early development and epigenetics: implications of the Chinese famine. Nat Rev Endocrinol. 2018;14(12):738–46. https://doi.org/10.1038/s41574-018-0106-1.

    Article  PubMed  Google Scholar 

  86. Kato M, Natarajan R. Diabetic nephropathy--emerging epigenetic mechanisms. Nat Rev Nephrol. 2014;10(9):517–30. https://doi.org/10.1038/nrneph.2014.116.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Ko YA, Mohtat D, Suzuki M, Park AS, Izquierdo MC, Han SY, et al. Cytosine methylation changes in enhancer regions of core pro-fibrotic genes characterize kidney fibrosis development. Genome Biol. 2013;14(10):R108. https://doi.org/10.1186/gb-2013-14-10-r108.

    Article  PubMed  PubMed Central  Google Scholar 

  88. •• Chu AY, Tin A, Schlosser P, Ko YA, Qiu C, Yao C, et al. Epigenome-wide association studies identify DNA methylation associated with kidney function. Nat Commun. 2017;8(1):1286. https://doi.org/10.1038/s41467-017-01297-7. This study identified key DNA methylation changes in peripheral blood cells that are associated with a decline of renal function in chronic kidney disease, and are also recapitulated in the kidney cortex biopsies from patients with kidney disease.

  89. • Qiu C, Hanson RL, Fufaa G, Kobes S, Gluck C, Huang J, et al. Cytosine methylation predicts renal function decline in American Indians. Kidney Int. 2018;93(6):1417–31. https://doi.org/10.1016/j.kint.2018.01.036. This study identified DNA methylation changes associated with impaired kidney function in the context of diabetic nephropathy in a cohort of Pima Indians with history of diabetes.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Pirola L, Balcerczyk A, Tothill RW, Haviv I, Kaspi A, Lunke S, et al. Genome-wide analysis distinguishes hyperglycemia regulated epigenetic signatures of primary vascular cells. Genome Res. 2011;21(10):1601–15. https://doi.org/10.1101/gr.116095.110.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Miao F, Wu X, Zhang L, Yuan YC, Riggs AD, Natarajan R. Genome-wide analysis of histone lysine methylation variations caused by diabetic conditions in human monocytes. J Biol Chem. 2007;282(18):13854–63. https://doi.org/10.1074/jbc.M609446200.

    Article  CAS  PubMed  Google Scholar 

  92. Villeneuve LM, Reddy MA, Lanting LL, Wang M, Meng L, Natarajan R. Epigenetic histone H3 lysine 9 methylation in metabolic memory and inflammatory phenotype of vascular smooth muscle cells in diabetes. Proc Natl Acad Sci U S A. 2008;105(26):9047–52. https://doi.org/10.1073/pnas.0803623105.

    Article  PubMed  PubMed Central  Google Scholar 

  93. Writing Team for the Diabetes C, Complications Trial/Epidemiology of Diabetes I, Complications Research G. Sustained effect of intensive treatment of type 1 diabetes mellitus on development and progression of diabetic nephropathy: the Epidemiology of Diabetes Interventions and Complications (EDIC) study. JAMA. 2003;290(16):2159–67. https://doi.org/10.1001/jama.290.16.2159.

    Article  Google Scholar 

  94. Chalmers J, Cooper ME. UKPDS and the legacy effect. N Engl J Med. 2008;359(15):1618–20. https://doi.org/10.1056/NEJMe0807625.

    Article  CAS  PubMed  Google Scholar 

  95. Kim ES, Isoda F, Kurland I, Mobbs CV. Glucose-induced metabolic memory in Schwann cells: prevention by PPAR agonists. Endocrinology. 2013;154(9):3054–66. https://doi.org/10.1210/en.2013-1097.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Kowluru RA, Mishra M. Epigenetic regulation of redox signaling in diabetic retinopathy: role of Nrf2. Free Radic Biol Med. 2017;103:155–64. https://doi.org/10.1016/j.freeradbiomed.2016.12.030.

    Article  CAS  PubMed  Google Scholar 

  97. Leung A, Amaram V, Natarajan R. Linking diabetic vascular complications with LncRNAs. Vasc Pharmacol. 2018;114:139–44. https://doi.org/10.1016/j.vph.2018.01.007.

    Article  CAS  Google Scholar 

  98. Leung A, Natarajan R. Long noncoding RNAs in diabetes and diabetic complications. Antioxid Redox Signal. 2018;29(11):1064–73. https://doi.org/10.1089/ars.2017.7315.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Kato M, Natarajan R. MicroRNAs in diabetic nephropathy: functions, biomarkers, and therapeutic targets. Ann N Y Acad Sci. 2015;1353:72–88. https://doi.org/10.1111/nyas.12758.

    Article  PubMed  PubMed Central  Google Scholar 

  100. Kato M, Putta S, Wang M, Yuan H, Lanting L, Nair I, et al. TGF-beta activates Akt kinase through a microRNA-dependent amplifying circuit targeting PTEN. Nat Cell Biol. 2009;11(7):881–9. https://doi.org/10.1038/ncb1897.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. •• Kato M, Wang M, Chen Z, Bhatt K, Oh HJ, Lanting L, et al. An endoplasmic reticulum stress-regulated lncRNA hosting a microRNA megacluster induces early features of diabetic nephropathy. Nat Commun. 2016;7:12864. https://doi.org/10.1038/ncomms12864. This study identified a novel, ER-stress senstive, non-coding RNA regulatory module in mesangial cells under diabetic conditions that induces key features of diabetic nephropathy, highlighting that cellular-stress can drive epigenetic dysregulation to drive the pathogenesis of T2D complications. It also illustrates the use of modified antisense oligonucleotides to target lncRNAs in vitro and in vivo in mice.

  102. • Das S, Reddy MA, Senapati P, Stapleton K, Lanting L, Wang M, et al. Diabetes Mellitus-Induced Long Noncoding RNA Dnm3os Regulates Macrophage Functions and Inflammation via Nuclear Mechanisms. Arterioscler Thromb Vasc Biol. 2018;38(8):1806–20. https://doi.org/10.1161/ATVBAHA.117.310663. The data presented in this study showcase the importance of altered lncRNA regulation in promoting inflammation and macrophage dysfunction in diabetes complications.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. •• Das S, Senapati P, Chen Z, Reddy MA, Ganguly R, Lanting L, et al. Regulation of angiotensin II actions by enhancers and super-enhancers in vascular smooth muscle cells. Nat Commun. 2017;8(1):1467. https://doi.org/10.1038/s41467-017-01629-7. This study exemplifies how the signaling by growth factors associated with diabetes complications epigenetically activates the enhancers and super-enhancers in the target cells to regulate the expression of the associated target genes, including lncRNAs.

  104. • Das S, Zhang E, Senapati P, Amaram V, Reddy MA, Stapleton K, et al. A Novel Angiotensin II-Induced Long Noncoding RNA Giver Regulates Oxidative Stress, Inflammation, and Proliferation in Vascular Smooth Muscle Cells. Circ Res. 2018;123(12):1298–312. https://doi.org/10.1161/CIRCRESAHA.118.313207. This study identifies a novel, Angiotesin II responsive lncRNA that regulates oxidative stress and inflammation in vascular smooth muscle cells in the context of hypertension. A human ortholog is upregulated in arteries of hypertensive subjects.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Miao F, Chen Z, Genuth S, Paterson A, Zhang L, Wu X, et al. Evaluating the role of epigenetic histone modifications in the metabolic memory of type 1 diabetes. Diabetes. 2014;63(5):1748–62. https://doi.org/10.2337/db13-1251.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  106. •• Chen Z, Miao F, Paterson AD, Lachin JM, Zhang L, Schones DE, et al. Epigenomic profiling reveals an association between persistence of DNA methylation and metabolic memory in the DCCT/EDIC type 1 diabetes cohort. Proc Natl Acad Sci U S A. 2016;113(21):E3002–11. https://doi.org/10.1073/pnas.1603712113. This study uncovered the epigenetic basis of metabolic memory in the landmark DCCT/EDIC diabetes clinical trial. The results identified novel mechanistic targets that display sustained differential epigenetic patterns (DNA methylation) in the same type 1 diabetic subjects over 16 years in asscoiation with glycemic history and an adverse diabetes complications outcome.

    Article  CAS  Google Scholar 

  107. •• Snyder MW, Kircher M, Hill AJ, Daza RM, Shendure J. Cell-free DNA Comprises an In Vivo Nucleosome Footprint that Informs Its Tissues-Of-Origin. Cell. 2016;164(1–2):57–68. https://doi.org/10.1016/j.cell.2015.11.050. This study shows that circulating cell-free DNA faithfully mirrors the epigenetic footprints of tissue-of-origin, highlighting the potential of cell-free DNA as a tool for monitoring tissue specific changes in disease.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  108. • Moss J, Magenheim J, Neiman D, Zemmour H, Loyfer N, Korach A, et al. Comprehensive human cell-type methylation atlas reveals origins of circulating cell-free DNA in health and disease. Nat Commun. 2018;9(1):5068. https://doi.org/10.1038/s41467-018-07466-6. This study developed a detailed human cell-type DNA-methylation atlas to advance the development of cell-free DNA based disease biomarkers.

  109. Akirav EM, Lebastchi J, Galvan EM, Henegariu O, Akirav M, Ablamunits V, et al. Detection of beta cell death in diabetes using differentially methylated circulating DNA. Proc Natl Acad Sci U S A. 2011;108(47):19018–23. https://doi.org/10.1073/pnas.1111008108.

    Article  PubMed  PubMed Central  Google Scholar 

  110. Husseiny MI, Kaye A, Zebadua E, Kandeel F, Ferreri K. Tissue-specific methylation of human insulin gene and PCR assay for monitoring beta cell death. PLoS One. 2014;9(4):e94591. https://doi.org/10.1371/journal.pone.0094591.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  111. Ronn T, Volkov P, Gillberg L, Kokosar M, Perfilyev A, Jacobsen AL, et al. Impact of age, BMI and HbA1c levels on the genome-wide DNA methylation and mRNA expression patterns in human adipose tissue and identification of epigenetic biomarkers in blood. Hum Mol Genet. 2015;24(13):3792–813. https://doi.org/10.1093/hmg/ddv124.

    Article  CAS  PubMed  Google Scholar 

  112. • Bacos K, Gillberg L, Volkov P, Olsson AH, Hansen T, Pedersen O, et al. Blood-based biomarkers of age-associated epigenetic changes in human islets associate with insulin secretion and diabetes. Nat Commun. 2016;7:11089. https://doi.org/10.1038/ncomms11089. This study illustrates the utility of blood-based biomarkers in predicting metabolic health, using islets as an example.

  113. Parrizas M, Novials A. Circulating microRNAs as biomarkers for metabolic disease. Best Pract Res Clin Endocrinol Metab. 2016;30(5):591–601. https://doi.org/10.1016/j.beem.2016.08.001.

    Article  CAS  PubMed  Google Scholar 

  114. Lin X, Qin Y, Jia J, Lin T, Lin X, Chen L, et al. miR-155 enhances insulin sensitivity by coordinated regulation of multiple genes in mice. PLoS Genet. 2016;12(10):e1006308. https://doi.org/10.1371/journal.pgen.1006308.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  115. •• Ying W, Riopel M, Bandyopadhyay G, Dong Y, Birmingham A, Seo JB, et al. Adipose tissue macrophage-derived exosomal miRNAs can modulate in vivo and in vitro insulin sensitivity. Cell. 2017;171(2):372–84 e12. https://doi.org/10.1016/j.cell.2017.08.035. This study identifies a novel role for exosomal miRNAs in T2D pathogenesis, and highlights their potential as predictive biomarkers.

    Article  PubMed  Google Scholar 

  116. Castano C, Kalko S, Novials A, Parrizas M. Obesity-associated exosomal miRNAs modulate glucose and lipid metabolism in mice. Proc Natl Acad Sci U S A. 2018;115(48):12158–63. https://doi.org/10.1073/pnas.1808855115.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  117. Fu W, Farache J, Clardy SM, Hattori K, Mander P, Lee K, et al. Epigenetic modulation of type-1 diabetes via a dual effect on pancreatic macrophages and beta cells. Elife. 2014;3:e04631. https://doi.org/10.7554/eLife.04631.

    Article  PubMed  PubMed Central  Google Scholar 

  118. Deeney JT, Belkina AC, Shirihai OS, Corkey BE, Denis GV. BET bromodomain proteins Brd2, Brd3 and Brd4 selectively regulate metabolic pathways in the pancreatic beta-cell. PLoS One. 2016;11(3):e0151329. https://doi.org/10.1371/journal.pone.0151329.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  119. Huijbregts L, Kjaer Petersen MB, Berthault C, Hansson M, Aiello V, Rachdi L, et al. Bromodomain and extra terminal proteins inhibitors promote pancreatic endocrine cell fate. Diabetes. 2019:db180224. https://doi.org/10.2337/db18-0224.

  120. •• Liu XS, Wu H, Ji X, Stelzer Y, Wu X, Czauderna S, et al. Editing DNA methylation in the mammalian genome. Cell. 2016;167(1):233–47 e17. https://doi.org/10.1016/j.cell.2016.08.056. This study presents a novel, locus specific epigenetic editing approach that can be leveraged to tailor the epigenetic signatures of disease specific epialleles towards potential therapeutic interventions.

    Article  PubMed  PubMed Central  Google Scholar 

  121. •• Ou K, Yu M, Moss NG, Wang YJ, Wang AW, Nguyen SC, et al. Targeted demethylation at the CDKN1C/p57 locus induces human beta cell replication. J Clin Invest. 2019;129(1):209–14. https://doi.org/10.1172/JCI99170. This study illustrates the power of using locus specific epigenetic tailoring to mimic specific physiological and epigenetic contexts to induce a therapeutically relevant outcome, in this case, the replication of human beta-cells, that are normally resistant to mitogenic cues.

    Article  PubMed  PubMed Central  Google Scholar 

  122. • Liu J, Banerjee A, Herring CA, Attalla J, Hu R, Xu Y, et al. Neurog3-independent methylation is the earliest detectable mark distinguishing pancreatic progenitor identity. Dev Cell. 2019;48(1):49–63 e7. https://doi.org/10.1016/j.devcel.2018.11.048. This study utilizes epigenetic tailoring to bias endocrine differentiation to beta cell fate.

    Article  PubMed  PubMed Central  Google Scholar 

  123. • Liao HK, Hatanaka F, Araoka T, Reddy P, Wu MZ, Sui Y, et al. In vivo target gene activation via CRISPR/Cas9-mediated trans-epigenetic modulation. Cell. 2017;171(7):1495–507 e15. https://doi.org/10.1016/j.cell.2017.10.025. This study presents a novel approach to epigenetic engineering, which involves the targeting of transcriptional regulatory complexes to specific loci to induce epigenetic remodeling.

    Article  PubMed  PubMed Central  Google Scholar 

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Funding

This review was funded by the National Institutes of Health (NIDDK and NHLBI), the Wanek Family Project to Cure Type 1 Diabetes at City of Hope, and the Juvenile Diabetes Research Foundation (to RN), and from the Wanek Family Project to Cure Type 1 Diabetes at City of Hope, Human Islet Research Network (NIH) UC4 DK104162, and the National Institutes of Health (NIDDK; R01 grant DK120523) (to SD).

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Correspondence to Rama Natarajan.

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Sangeeta Dhawan declares no conflict of interest.

Rama Natarajan reports a pending patent on inhibitors of epigenetically modified targets.

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All the studies noted in this review that were performed by the authors involving animals were done in compliance with appropriate institutional committees for animal research (IACUC), and all institutional guidelines for the care and use of animals were followed. Studies quoted in this article undertaken by the authors involving human subjects were either carried out on retrospective deidentified samples obtained from appropriate repositories, in compliance with institutional review boards (IRB), or all the procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional review boards (IRB), and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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This article is part of the Topical Collection on Pathogenesis of Type 2 Diabetes and Insulin Resistance

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Dhawan, S., Natarajan, R. Epigenetics and Type 2 Diabetes Risk. Curr Diab Rep 19, 47 (2019). https://doi.org/10.1007/s11892-019-1168-8

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