Review Article | Published:

Epigenetics and epigenomics in diabetic kidney disease and metabolic memory

Nature Reviews Nephrology (2019) | Download Citation


The development and progression of diabetic kidney disease (DKD), a highly prevalent complication of diabetes mellitus, are influenced by both genetic and environmental factors. DKD is an important contributor to the morbidity of patients with diabetes mellitus, indicating a clear need for an improved understanding of disease aetiology to inform the development of more efficacious treatments. DKD is characterized by an accumulation of extracellular matrix, hypertrophy and fibrosis in kidney glomerular and tubular cells. Increasing evidence shows that genes associated with these features of DKD are regulated not only by classical signalling pathways but also by epigenetic mechanisms involving chromatin histone modifications, DNA methylation and non-coding RNAs. These mechanisms can respond to changes in the environment and, importantly, might mediate the persistent long-term expression of DKD-related genes and phenotypes induced by prior glycaemic exposure despite subsequent glycaemic control, a phenomenon called metabolic memory. Detection of epigenetic events during the early stages of DKD could be valuable for timely diagnosis and prompt treatment to prevent progression to end-stage renal disease. Identification of epigenetic signatures of DKD via epigenome-wide association studies might also inform precision medicine approaches. Here, we highlight the emerging role of epigenetics and epigenomics in DKD and the translational potential of candidate epigenetic factors and non-coding RNAs as biomarkers and drug targets for DKD.

Key points

  • Diabetic kidney disease (DKD), involving the accumulation of extracellular matrix, hypertrophy and fibrosis in kidney glomerular and tubular cells, can lead to end-stage renal disease.

  • Genes associated with DKD are regulated not only by classical signalling pathways and transcription factors but also by epigenetic mechanisms, including chromatin histone modifications, DNA methylation and non-coding RNAs.

  • Metabolic memory is a phenomenon characterized by the persistent expression of DKD-related genes and phenotypes induced by glycaemic exposure despite subsequent glycaemic control.

  • Persistent epigenetic changes (DNA methylation and histone modifications) and signalling circuitry mediated by non-coding RNAs may be involved in metabolic memory.

  • Targeting epigenetic factors (using small molecules or locus-specific epigenetic editing via the CRISPR–Cas9 system) or non-coding RNAs (using chemically modified antisense oligonucleotides) are potential approaches to prevent or treat DKD and erase metabolic memory.

  • Epigenetic profiling through epigenome-wide association studies and RNA (transcriptome) profiling of patient samples (blood, urine and biopsy samples) might facilitate a precision (personalized) medicine approach for the treatment of DKD.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Additional information

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Nephroseq database:

Gene Expression Omnibus (GEO) database:


  1. 1.

    NCD Risk Factor Collaboration. Worldwide trends in diabetes since 1980: a pooled analysis of 751 population-based studies with 4·4 million participants. Lancet 387, 1513–1530 (2016).

  2. 2.

    Zimmet, P. Z., Magliano, D. J., Herman, W. H. & Shaw, J. E. Diabetes: a 21st century challenge. Lancet Diabetes Endocrinol. 2, 56–64 (2014).

  3. 3.

    Nathan, D. M. Long-term complications of diabetes mellitus. N. Engl. J. Med. 328, 1676–1685 (1993).

  4. 4.

    Rask-Madsen, C. & King, G. L. Vascular complications of diabetes: mechanisms of injury and protective factors. Cell Metab. 17, 20–33 (2013).

  5. 5.

    Forbes, J. M. & Cooper, M. E. Mechanisms of diabetic complications. Physiol. Rev. 93, 137–188 (2013).

  6. 6.

    Shah, M. S. & Brownlee, M. Molecular and cellular mechanisms of cardiovascular disorders in diabetes. Circ. Res. 118, 1808–1829 (2016).

  7. 7.

    Nathan, D. M. Diabetes: advances in diagnosis and treatment. JAMA 314, 1052–1062 (2015).

  8. 8.

    Gregg, E. W. et al. Changes in diabetes-related complications in the United States, 1990–2010. N. Engl. J. Med. 370, 1514–1523 (2014).

  9. 9.

    Alicic, R. Z., Rooney, M. T. & Tuttle, K. R. Diabetic kidney disease: challenges, progress, and possibilities. Clin. J. Am. Soc. Nephrol. 12, 2032–2045 (2017).

  10. 10.

    Fineberg, D., Jandeleit-Dahm, K. A. M. & Cooper, M. E. Diabetic nephropathy: diagnosis and treatment. Nat. Rev. Endocrinol. 9, 713–723 (2013).

  11. 11.

    Jones, C. A. et al. Epidemic of end-stage renal disease in people with diabetes in the United States population: do we know the cause? Kidney Int. 67, 1684–1691 (2005).

  12. 12.

    Park, C. W. Diabetic kidney disease: from epidemiology to clinical perspectives. Diabetes Metab. J. 38, 252–260 (2014).

  13. 13.

    Kanwar, Y. S., Sun, L., Xie, P., Liu, F. Y. & Chen, S. A glimpse of various pathogenetic mechanisms of diabetic nephropathy. Annu. Rev. Pathol. 6, 395–423 (2011).

  14. 14.

    Kato, M. & Natarajan, R. Diabetic nephropathy—emerging epigenetic mechanisms. Nat. Rev. Nephrol. 10, 517–530 (2014).

  15. 15.

    Meng, X.-M., Nikolic-Paterson, D. J. & Lan, H. Y. TGF-β: the master regulator of fibrosis. Nat. Rev. Nephrol. 12, 325 (2016).

  16. 16.

    Reidy, K., Kang, H. M., Hostetter, T. & Susztak, K. Molecular mechanisms of diabetic kidney disease. J. Clin. Invest. 124, 2333–2340 (2014).

  17. 17.

    Russo, V. E., Martienssen, R. A. & Riggs, A. D. Epigenetic Mechanisms of Gene Regulation (Cold Spring Harbor Laboratory Press, 1996).

  18. 18.

    Berger, S. L., Kouzarides, T., Shiekhattar, R. & Shilatifard, A. An operational definition of epigenetics. Genes Dev. 23, 781–783 (2009).

  19. 19.

    Keating, S. T., van Diepen, J. A., Riksen, N. P. & El-Osta, A. Epigenetics in diabetic nephropathy, immunity and metabolism. Diabetologia 61, 6–20 (2018).

  20. 20.

    Susztak, K. Understanding the epigenetic syntax for the genetic alphabet in the kidney. J. Am. Soc. Nephrol. 25, 10–17 (2014).

  21. 21.

    Chen, S., Jim, B. & Ziyadeh, F. N. Diabetic nephropathy and transforming growth factor-beta: transforming our view of glomerulosclerosis and fibrosis build-up. Semin. Nephrol. 23, 532–543 (2003).

  22. 22.

    Qian, Y., Feldman, E., Pennathur, S., Kretzler, M. & Brosius, F. C. III. From fibrosis to sclerosis: mechanisms of glomerulosclerosis in diabetic nephropathy. Diabetes 57, 1439–1445 (2008).

  23. 23.

    Pagtalunan, M. E. et al. Podocyte loss and progressive glomerular injury in type II diabetes. J. Clin. Invest. 99, 342–348 (1997).

  24. 24.

    Ruggenenti, P., Cravedi, P. & Remuzzi, G. The RAAS in the pathogenesis and treatment of diabetic nephropathy. Nat. Rev. Nephrol. 6, 319–330 (2010).

  25. 25.

    Abboud, H. E. Role of platelet-derived growth factor in renal injury. Annu. Rev. Physiol. 57, 297–309 (1995).

  26. 26.

    Sharma, K. & Ziyadeh, F. N. Hyperglycemia and diabetic kidney disease. The case for transforming growth factor-beta as a key mediator. Diabetes 44, 1139–1146 (1995).

  27. 27.

    Yamamoto, T., Nakamura, T., Noble, N. A., Ruoslahti, E. & Border, W. A. Expression of transforming growth factor beta is elevated in human and experimental diabetic nephropathy. Proc. Natl Acad. Sci. USA 90, 1814–1818 (1993).

  28. 28.

    Kato, M. et al. TGF-beta activates Akt kinase through a microRNA-dependent amplifying circuit targeting PTEN. Nat. Cell Biol. 11, 881–889 (2009).

  29. 29.

    Kato, M. et al. Role of the Akt/FoxO3a pathway in TGF-beta1-mediated mesangial cell dysfunction: a novel mechanism related to diabetic kidney disease. J. Am. Soc. Nephrol. 17, 3325–3335 (2006).

  30. 30.

    Kato, M. et al. TGF-beta induces acetylation of chromatin and of Ets-1 to alleviate repression of miR-192 in diabetic nephropathy. Sci. Signal. 6, ra43 (2013).

  31. 31.

    Kato, M. et al. An endoplasmic reticulum stress-regulated lncRNA hosting a microRNA megacluster induces early features of diabetic nephropathy. Nat. Commun. 7, 12864 (2016).

  32. 32.

    Sedeek, M. et al. Oxidative stress, Nox isoforms and complications of diabetes—potential targets for novel therapies. J. Cardiovasc. Transl Res. 5, 509–518 (2012).

  33. 33.

    Inagi, R., Ishimoto, Y. & Nangaku, M. Proteostasis in endoplasmic reticulum—new mechanisms in kidney disease. Nat. Rev. Nephrol. 10, 369–378 (2014).

  34. 34.

    Kropski, J. A. & Blackwell, T. S. Endoplasmic reticulum stress in the pathogenesis of fibrotic disease. J. Clin. Invest. 128, 64–73 (2018).

  35. 35.

    Brownlee, M. Biochemistry and molecular cell biology of diabetic complications. Nature 414, 813–820 (2001).

  36. 36.

    Deshpande, S. et al. Reduced autophagy by a microrna-mediated signaling cascade in diabetes-induced renal glomerular hypertrophy. Sci. Rep. 8, 6954 (2018).

  37. 37.

    Komorowsky, C. V., Brosius, F. C. III, Pennathur, S. & Kretzler, M. Perspectives on systems biology applications in diabetic kidney disease. J. Cardiovasc. Transl Res. 5, 491–508 (2012).

  38. 38.

    Brosius, F. C. III & Alpers, C. E. New targets for treatment of diabetic nephropathy: what we have learned from animal models. Curr. Opin. Nephrol. Hypertens. 22, 17–25 (2013).

  39. 39.

    Woroniecka, K. I. et al. Transcriptome analysis of human diabetic kidney disease. Diabetes 60, 2354–2369 (2011).

  40. 40.

    Brosius, F. C., Tuttle, K. R. & Kretzler, M. JAK inhibition in the treatment of diabetic kidney disease. Diabetologia 59, 1624–1627 (2016).

  41. 41.

    Tuttle, K. R. et al. JAK1/JAK2 inhibition by baricitinib in diabetic kidney disease: results from a Phase 2 randomized controlled clinical trial. Nephrol. Dial. Transplant. 33, 1950–1959 (2018).

  42. 42.

    Pena, M. J. et al. The effects of atrasentan on urinary metabolites in patients with type 2 diabetes and nephropathy. Diabetes Obes. Metab. 19, 749–753 (2017).

  43. 43.

    Nathan, D. M. et al. Intensive diabetes treatment and cardiovascular disease in patients with type 1 diabetes. N. Engl. J. Med. 353, 2643–2653 (2005).

  44. 44.

    Writing Team for the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Research Group. 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 290, 2159–2167 (2003).

  45. 45.

    de Boer, I. H. et al. Intensive diabetes therapy and glomerular filtration rate in type 1 diabetes. N. Engl. J. Med. 365, 2366–2376 (2011).

  46. 46.

    de Boer, I. H. & DCCT/EDIC Research Group. Kidney Disease and Related Findings in the Diabetes Control and Complications trial/Epidemiology of Diabetes Interventions and Complications study. Diabetes Care 37, 24–30 (2014).

  47. 47.

    Nathan, D. M. The Diabetes Control and Complications trial/Epidemiology of Diabetes Interventions and Complications study at 30 years: overview. Diabetes Care 37, 9–16 (2014).

  48. 48.

    Colagiuri, S., Cull, C. A. & Holman, R. R. Are lower fasting plasma glucose levels at diagnosis of type 2 diabetes associated with improved outcomes? UK Prospective Diabetes study 61. Diabetes Care 25, 1410–1417 (2002).

  49. 49.

    Thomas, M. C., Groop, P. H. & Tryggvason, K. Towards understanding the inherited susceptibility for nephropathy in diabetes. Curr. Opin. Nephrol. Hypertens. 21, 195–202 (2012).

  50. 50.

    Sandholm, N. et al. New susceptibility loci associated with kidney disease in type 1 diabetes. PLOS Genet. 8, e1002921 (2012).

  51. 51.

    Sandholm, N. et al. The genetic landscape of renal complications in type 1 diabetes. J. Am. Soc. Nephrol. 28, 557–574 (2017).

  52. 52.

    van Zuydam, N. R. et al. A genome-wide association study of diabetic kidney disease in subjects with type 2 diabetes. Diabetes 67, 1414–1427 (2018).

  53. 53.

    Cooper, M. E. & El-Osta, A. Epigenetics: mechanisms and implications for diabetic complications. Circ. Res. 107, 1403–1413 (2010).

  54. 54.

    Jirtle, R. L. & Skinner, M. K. Environmental epigenomics and disease susceptibility. Nat. Rev. Genet. 8, 253–262 (2007).

  55. 55.

    Feinberg, A. The key role of epigenetics in human disease. N. Engl. J. Med. 379, 400–401 (2018).

  56. 56.

    Rakyan, V. K., Down, T. A., Balding, D. J. & Beck, S. Epigenome-wide association studies for common human diseases. Nat. Rev. Genet. 12, 529 (2011).

  57. 57.

    Maurano, M. T. et al. Systematic localization of common disease-associated variation in regulatory DNA. Science 337, 1190–1195 (2012).

  58. 58.

    Qiu, C. et al. Renal compartment–specific genetic variation analyses identify new pathways in chronic kidney disease. Nat. Med. 24, 1721–1731 (2018).

  59. 59.

    Kouzarides, T. Chromatin modifications and their function. Cell 128, 693–705 (2007).

  60. 60.

    Jones, P. A. Functions of DNA methylation: islands, start sites, gene bodies and beyond. Nat. Rev. Genet. 13, 484–492 (2012).

  61. 61.

    Portela, A. & Esteller, M. Epigenetic modifications and human disease. Nat. Biotechnol. 28, 1057–1068 (2010).

  62. 62.

    Simmons, R. Epigenetics and maternal nutrition: nature v. nurture. Proc. Nutr. Soc. 70, 73–81 (2011).

  63. 63.

    Woroniecki, R., Gaikwad, A. B. & Susztak, K. Fetal environment, epigenetics, and pediatric renal disease. Pediatr. Nephrol. 26, 705–711 (2011).

  64. 64.

    Wanner, N. et al. DNA methyltransferase 1 controls nephron progenitor cell renewal and differentiation. J. Am. Soc. Nephrol. 30, 63–78 (2019).

  65. 65.

    Rosen, E. D. et al. Epigenetics and epigenomics: implications for diabetes and obesity. Diabetes 67, 1923–1931 (2018).

  66. 66.

    Rakyan, V. K. et al. Identification of type 1 diabetes-associated DNA methylation variable positions that precede disease diagnosis. PLOS Genet. 7, e1002300 (2011).

  67. 67.

    Davegardh, C., Garcia-Calzon, S., Bacos, K. & Ling, C. DNA methylation in the pathogenesis of type 2 diabetes in humans. Mol. Metab. 14, 12–25 (2018).

  68. 68.

    Schaefer, M. et al. RNA methylation by Dnmt2 protects transfer RNAs against stress-induced cleavage. Genes Dev. 24, 1590–1595 (2010).

  69. 69.

    Tahiliani, M. et al. Conversion of 5-methylcytosine to 5-hydroxymethylcytosine in mammalian DNA by MLL partner TET1. Science 324, 930–935 (2009).

  70. 70.

    Wanner, N. & Bechtel-Walz, W. Epigenetics of kidney disease. Cell Tissue Res. 369, 75–92 (2017).

  71. 71.

    Bechtel, W. et al. Methylation determines fibroblast activation and fibrogenesis in the kidney. Nat. Med. 16, 544–550 (2010).

  72. 72.

    Tampe, B. et al. Tet3-mediated hydroxymethylation of epigenetically silenced genes contributes to bone morphogenic protein 7-induced reversal of kidney fibrosis. J. Am. Soc. Nephrol. 25, 905–912 (2014).

  73. 73.

    Hasegawa, K. et al. Renal tubular Sirt1 attenuates diabetic albuminuria by epigenetically suppressing Claudin-1 overexpression in podocytes. Nat. Med. 19, 1496–1504 (2013).

  74. 74.

    Hayashi, K. et al. KLF4-dependent epigenetic remodeling modulates podocyte phenotypes and attenuates proteinuria. J. Clin. Invest. 124, 2523–2537 (2014).

  75. 75.

    Marumo, T. et al. Diabetes induces aberrant DNA methylation in the proximal tubules of the kidney. J. Am. Soc. Nephrol. 26, 2388–2397 (2015).

  76. 76.

    Sharma, I., Dutta, R. K., Singh, N. K. & Kanwar, Y. S. High glucose-induced hypomethylation promotes binding of Sp-1 to myo-inositol oxygenase: implication in the pathobiology of diabetic tubulopathy. Am. J. Pathol. 187, 724–739 (2017).

  77. 77.

    Zhang, L. et al. DNA methyltransferase 1 may be a therapy target for attenuating diabetic nephropathy and podocyte injury. Kidney Int. 92, 140–153 (2017).

  78. 78.

    Yang, L. et al. Effect of TET2 on the pathogenesis of diabetic nephropathy through activation of transforming growth factor beta1 expression via DNA demethylation. Life Sci. 207, 127–137 (2018).

  79. 79.

    Oba, S. et al. Aberrant DNA methylation of Tgfb1 in diabetic kidney mesangial cells. Sci. Rep. 8, 16338 (2018).

  80. 80.

    Bell, C. G. et al. Genome-wide DNA methylation analysis for diabetic nephropathy in type 1 diabetes mellitus. BMC Med. Genomics 3, 33 (2010).

  81. 81.

    Sapienza, C. et al. DNA methylation profiling identifies epigenetic differences between diabetes patients with ESRD and diabetes patients without nephropathy. Epigenetics 6, 20–28 (2011).

  82. 82.

    Bomotti, S. M. et al. Epigenetic markers of renal function in African Americans. Nurs. Res. Pract. 2013, 687519 (2013).

  83. 83.

    Dirks, R. A., Stunnenberg, H. G. & Marks, H. Genome-wide epigenomic profiling for biomarker discovery. Clin. Epigenetics 8, 122 (2016).

  84. 84.

    Ko, Y. A. et al. Cytosine methylation changes in enhancer regions of core pro-fibrotic genes characterize kidney fibrosis development. Genome Biol. 14, R108 (2013).

  85. 85.

    Smyth, L. J., McKay, G. J., Maxwell, A. P. & McKnight, A. J. DNA hypermethylation and DNA hypomethylation is present at different loci in chronic kidney disease. Epigenetics 9, 366–376 (2014).

  86. 86.

    Swan, E. J., Maxwell, A. P. & McKnight, A. J. Distinct methylation patterns in genes that affect mitochondrial function are associated with kidney disease in blood-derived DNA from individuals with type 1 diabetes. Diabet Med. 32, 1110–1115 (2015).

  87. 87.

    Wing, M. R. et al. DNA methylation profile associated with rapid decline in kidney function: findings from the CRIC study. Nephrol. Dial. Transplant. 29, 864–872 (2014).

  88. 88.

    Block, T. & El-Osta, A. Epigenetic programming, early life nutrition and the risk of metabolic disease. Atherosclerosis 266, 31–40 (2017).

  89. 89.

    Gautier, J. F. et al. Kidney dysfunction in adult offspring exposed in utero to type 1 diabetes is associated with alterations in genome-wide DNA methylation. PLOS ONE 10, e0134654 (2015).

  90. 90.

    Chu, A. Y. et al. Epigenome-wide association studies identify DNA methylation associated with kidney function. Nat. Commun. 8, 1286 (2017).

  91. 91.

    Qiu, C. et al. Cytosine methylation predicts renal function decline in American Indians. Kidney Int. 93, 1417–1431 (2018).

  92. 92.

    Wang, Y.-Z. et al. Specific expression network analysis of diabetic nephropathy kidney tissue revealed key methylated sites. J. Cell. Physiol. 233, 7139–7147 (2018).

  93. 93.

    Houseman, E. A. et al. DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics 13, 86 (2012).

  94. 94.

    Wu, M. C. & Kuan, P. F. A. Guide to Illumina BeadChip data analysis. Methods Mol. Biol. 1708, 303–330 (2018).

  95. 95.

    Goodwin, S., McPherson, J. D. & McCombie, W. R. Coming of age: ten years of next-generation sequencing technologies. Nat. Rev. Genet. 17, 333 (2016).

  96. 96.

    Stuart, T. & Satija, R. Integrative single-cell analysis. Nat. Rev. Genet. (2019).

  97. 97.

    Park, J. et al. Single-cell transcriptomics of the mouse kidney reveals potential cellular targets of kidney disease. Science 360, 758–763 (2018).

  98. 98.

    Wu, H., Kirita, Y., Donnelly, E. L. & Humphreys, B. D. Advantages of single-nucleus over single-cell rna sequencing of adult kidney: rare cell types and novel cell states revealed in fibrosis. J. Am. Soc. Nephrol. 30, 23–32 (2019).

  99. 99.

    Karaiskos, N. et al. A Single-cell transcriptome atlas of the mouse glomerulus. J. Am. Soc. Nephrol. 29, 2060–2068 (2018).

  100. 100.

    Wu, H. et al. Single-cell transcriptomics of a human kidney allograft biopsy specimen defines a diverse inflammatory response. J. Am. Soc. Nephrol. 29, 2069–2080 (2018).

  101. 101.

    EncodeProjectConsortium. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57–74 (2012).

  102. 102.

    Zhou, V. W., Goren, A. & Bernstein, B. E. Charting histone modifications and the functional organization of mammalian genomes. Nat. Rev. Genet. 12, 7–18 (2011).

  103. 103.

    Jin, F., Li, Y., Ren, B. & Natarajan, R. Enhancers: multi-dimensional signal integrators. Transcription 2, 226–230 (2011).

  104. 104.

    Hnisz, D. et al. Super-enhancers in the control of cell identity and disease. Cell 155, 934–947 (2013).

  105. 105.

    Reinberg, D. & Vales, L. D. Chromatin domains rich in inheritance. Science 361, 33–34 (2018).

  106. 106.

    Klose, R. J. & Zhang, Y. Regulation of histone methylation by demethylimination and demethylation. Nat. Rev. Mol. Cell. Biol. 8, 307–318 (2007).

  107. 107.

    Filippakopoulos, P. & Knapp, S. Targeting bromodomains: epigenetic readers of lysine acetylation. Nat. Rev. Drug Discov. 13, 337–356 (2014).

  108. 108.

    Marmorstein, R. & Zhou, M. M. Writers and readers of histone acetylation: structure, mechanism, and inhibition. Cold Spring Harb. Perspect. Biol. 6, a018762 (2014).

  109. 109.

    Zhao, S. et al. Regulation of cellular metabolism by protein lysine acetylation. Science 327, 1000–1004 (2010).

  110. 110.

    Zhang, H. & Pollin, T. I. Epigenetics variation and pathogenesis in diabetes. Curr. Diab. Rep. 18, 121 (2018).

  111. 111.

    Smith, C. J. & Ryckman, K. K. Epigenetic and developmental influences on the risk of obesity, diabetes, and metabolic syndrome. Diabetes Metab. Syndr. Obes. 8, 295–302 (2015).

  112. 112.

    Yuan, H. et al. Involvement of p300/CBP and epigenetic histone acetylation in TGF-beta1-mediated gene transcription in mesangial cells. Am. J. Physiol. Renal Physiol. 304, F601–F613 (2013).

  113. 113.

    Sun, G. et al. Epigenetic histone methylation modulates fibrotic gene expression. J. Am. Soc. Nephrol. 21, 2069–2080 (2010).

  114. 114.

    Yuan, H. et al. Epigenetic histone modifications involved in profibrotic gene regulation by 12/15-lipoxygenase and its oxidized lipid products in diabetic nephropathy. Antioxid. Redox Signal. 24, 361–375 (2016).

  115. 115.

    Chung, A. C., Huang, X. R., Meng, X. & Lan, H. Y. miR-192 mediates TGF-beta/Smad3-driven renal fibrosis. J. Am. Soc. Nephrol. 21, 1317–1325 (2010).

  116. 116.

    Kato, M. et al. MicroRNA-192 in diabetic kidney glomeruli and its function in TGF-beta-induced collagen expression via inhibition of E-box repressors. Proc. Natl Acad. Sci. USA 104, 3432–3437 (2007).

  117. 117.

    Reddy, M. A. et al. Losartan reverses permissive epigenetic changes in renal glomeruli of diabetic db/db mice. Kidney Int. 85, 362–373 (2014).

  118. 118.

    Komers, R. et al. Epigenetic changes in renal genes dysregulated in mouse and rat models of type 1 diabetes. Lab. Invest. 93, 543–552 (2013).

  119. 119.

    Majumder, S. et al. Shifts in podocyte histone H3K27me3 regulate mouse and human glomerular disease. J. Clin. Invest. 128, 483–499 (2018).

  120. 120.

    Giacco, F. & Brownlee, M. Oxidative stress and diabetic complications. Circ. Res. 107, 1058–1070 (2010).

  121. 121.

    Miao, F., Gonzalo, I. G., Lanting, L. & Natarajan, R. In vivo chromatin remodeling events leading to inflammatory gene transcription under diabetic conditions. J. Biol. Chem. 279, 18091–18097 (2004).

  122. 122.

    Miao, F. et al. Genome-wide analysis of histone lysine methylation variations caused by diabetic conditions in human monocytes. J. Biol. Chem. 282, 13854–13863 (2007).

  123. 123.

    Miao, F. et al. Lymphocytes from patients with type 1 diabetes display a distinct profile of chromatin histone H3 lysine 9 dimethylation: an epigenetic study in diabetes. Diabetes 57, 3189–3198 (2008).

  124. 124.

    Li, Y. et al. Role of the histone H3 lysine 4 methyltransferase, SET7/9, in the regulation of NF-kappaB-dependent inflammatory genes. Relevance to diabetes and inflammation. J. Biol. Chem. 283, 26771–26781 (2008).

  125. 125.

    Okabe, J. et al. Endothelial transcriptome in response to pharmacological methyltransferase inhibition. ChemMedChem 9, 1755–1762 (2014).

  126. 126.

    Miao, F. et al. Evaluating the role of epigenetic histone modifications in the metabolic memory of type 1 diabetes. Diabetes 63, 1748–1762 (2014).

  127. 127.

    Chen, Z. 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. USA 113, E3002–E3011 (2016).

  128. 128.

    Shalev, A. Thioredoxin-interacting protein: regulation and function in the pancreatic beta-cell. Mol. Endocrinol. 28, 1211–1220 (2014).

  129. 129.

    Walaszczyk, E. 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 61, 354–368 (2018).

  130. 130.

    Villeneuve, L. M. et al. Epigenetic histone H3 lysine 9 methylation in metabolic memory and inflammatory phenotype of vascular smooth muscle cells in diabetes. Proc. Natl Acad. Sci. USA 105, 9047–9052 (2008).

  131. 131.

    Villeneuve, L. M. et al. Enhanced levels of microRNA-125b in vascular smooth muscle cells of diabetic db/db mice lead to increased inflammatory gene expression by targeting the histone methyltransferase Suv39h1. Diabetes 59, 2904–2915 (2010).

  132. 132.

    El-Osta, A. et al. Transient high glucose causes persistent epigenetic changes and altered gene expression during subsequent normoglycemia. J. Exp. Med. 205, 2409–2417 (2008).

  133. 133.

    Tonna, S., El-Osta, A., Cooper, M. E. & Tikellis, C. Metabolic memory and diabetic nephropathy: potential role for epigenetic mechanisms. Nat. Rev. Nephrol. 6, 332–341 (2010).

  134. 134.

    Brasacchio, D. et al. Hyperglycemia induces a dynamic cooperativity of histone methylase and demethylase enzymes associated with gene-activating epigenetic marks that coexist on the lysine tail. Diabetes 58, 1229–1236 (2009).

  135. 135.

    Okabe, J. et al. Distinguishing hyperglycemic changes by Set7 in vascular endothelial cells. Circ. Res. 110, 1067–1076 (2012).

  136. 136.

    Reddy, M. A., Zhang, E. & Natarajan, R. Epigenetic mechanisms in diabetic complications and metabolic memory. Diabetologia 58, 443–455 (2015).

  137. 137.

    Heyn, H. & Esteller, M. An adenine code for DNA: a second life for N6-methyladenine. Cell 161, 710–713 (2015).

  138. 138.

    Bertero, A. et al. The SMAD2/3 interactome reveals that TGFβ controls m6A mRNA methylation in pluripotency. Nature 555, 256 (2018).

  139. 139.

    Guttman, M. et al. Chromatin signature reveals over a thousand highly conserved large non-coding RNAs in mammals. Nature 458, 223–227 (2009).

  140. 140.

    Carninci, P. et al. The transcriptional landscape of the mammalian genome. Science 309, 1559–1563 (2005).

  141. 141.

    Bartel, D. P. Metazoan microRNAs. Cell 173, 20–51 (2018).

  142. 142.

    Harvey, S. J. et al. Podocyte-specific deletion of dicer alters cytoskeletal dynamics and causes glomerular disease. J. Am. Soc. Nephrol. 19, 2150–2158 (2008).

  143. 143.

    Ho, J. et al. Podocyte-specific loss of functional microRNAs leads to rapid glomerular and tubular injury. J. Am. Soc. Nephrol. 19, 2069–2075 (2008).

  144. 144.

    Shi, S. et al. Podocyte-selective deletion of dicer induces proteinuria and glomerulosclerosis. J. Am. Soc. Nephrol. 19, 2159–2169 (2008).

  145. 145.

    Nagalakshmi, V. K. et al. Dicer regulates the development of nephrogenic and ureteric compartments in the mammalian kidney. Kidney Int. 79, 317–330 (2011).

  146. 146.

    Zhdanova, O. et al. The inducible deletion of Drosha and microRNAs in mature podocytes results in a collapsing glomerulopathy. Kidney Int. 80, 719–730 (2011).

  147. 147.

    Putta, S. et al. Inhibiting microRNA-192 ameliorates renal fibrosis in diabetic nephropathy. J. Am. Soc. Nephrol. 23, 458–469 (2012).

  148. 148.

    Deshpande, S. D. et al. Transforming growth factor-beta-induced cross talk between p53 and a microRNA in the pathogenesis of diabetic nephropathy. Diabetes 62, 3151–3162 (2013).

  149. 149.

    Kato, M. & Natarajan, R. MicroRNAs in diabetic nephropathy: functions, biomarkers, and therapeutic targets. Ann. NY Acad. Sci. 1353, 72–88 (2015).

  150. 150.

    Trionfini, P. & Benigni, A. MicroRNAs as master regulators of glomerular function in health and disease. J. Am. Soc. Nephrol. 28, 1686–1696 (2017).

  151. 151.

    Trionfini, P., Benigni, A. & Remuzzi, G. MicroRNAs in kidney physiology and disease. Nat. Rev. Nephrol. 11, 23–33 (2015).

  152. 152.

    Cheng, T. L. et al. MeCP2 suppresses nuclear microRNA processing and dendritic growth by regulating the DGCR8/Drosha complex. Dev. Cell 28, 547–560 (2014).

  153. 153.

    Oh, H. J. et al. Inhibition of the processing of miR-25 by HIPK2-Phosphorylated-MeCP2 induces NOX4 in early diabetic nephropathy. Sci. Rep. 6, 38789 (2016).

  154. 154.

    Cabili, M. N. et al. Integrative annotation of human large intergenic noncoding RNAs reveals global properties and specific subclasses. Genes Dev. 25, 1915–1927 (2011).

  155. 155.

    Wapinski, O. & Chang, H. Y. Long noncoding RNAs and human disease. Trends Cell Biol. 21, 354–361 (2011).

  156. 156.

    Taft, R. J., Pang, K. C., Mercer, T. R., Dinger, M. & Mattick, J. S. Non-coding RNAs: regulators of disease. J. Pathol. 220, 126–139 (2010).

  157. 157.

    Moran, V. A., Perera, R. J. & Khalil, A. M. Emerging functional and mechanistic paradigms of mammalian long non-coding RNAs. Nucleic Acids Res. 40, 6391–6400 (2012).

  158. 158.

    Wilusz, J. E., Sunwoo, H. & Spector, D. L. Long noncoding RNAs: functional surprises from the RNA world. Genes Dev. 23, 1494–1504 (2009).

  159. 159.

    Moran, I. et al. Human beta cell transcriptome analysis uncovers lncRNAs that are tissue-specific, dynamically regulated, and abnormally expressed in type 2 diabetes. Cell Metab. 16, 435–448 (2012).

  160. 160.

    Leung, A., Amaram, V. & Natarajan, R. Linking diabetic vascular complications with LncRNAs. Vascul. Pharmacol. (2018).

  161. 161.

    Leung, A. et al. Novel long noncoding RNAs are regulated by angiotensin II in vascular smooth muscle cells. Circ. Res. 113, 266–278 (2013).

  162. 162.

    Das, S. et al. A novel angiotensin II-induced long noncoding RNA giver regulates oxidative stress, inflammation, and proliferation in vascular smooth muscle cells. Circ. Res. 123, 1298–1312 (2018).

  163. 163.

    Das, S. et al. Regulation of angiotensin II actions by enhancers and super-enhancers in vascular smooth muscle cells. Nat. Commun. 8, 1467 (2017).

  164. 164.

    Alvarez, M. L. & DiStefano, J. K. Functional characterization of the plasmacytoma variant translocation 1 gene (PVT1) in diabetic nephropathy. PLOS ONE 6, e18671 (2011).

  165. 165.

    Hanson, R. L. et al. Identification of PVT1 as a candidate gene for end-stage renal disease in type 2 diabetes using a pooling-based genome-wide single nucleotide polymorphism association study. Diabetes 56, 975–983 (2007).

  166. 166.

    Alvarez, M. L., Khosroheidari, M., Eddy, E. & Kiefer, J. Role of microRNA 1207-5P and its host gene, the long non-coding RNA Pvt1, as mediators of extracellular matrix accumulation in the kidney: implications for diabetic nephropathy. PLOS ONE 8, e77468 (2013).

  167. 167.

    Zhou, Q. et al. Identification of novel long noncoding RNAs associated with TGF-beta/Smad3-mediated renal inflammation and fibrosis by RNA sequencing. Am. J. Pathol. 184, 409–417 (2014).

  168. 168.

    Long, J. et al. Long noncoding RNA Tug1 regulates mitochondrial bioenergetics in diabetic nephropathy. J. Clin. Invest. 126, 4205–4218 (2016).

  169. 169.

    Sun, S. F. et al. Novel lncRNA Erbb4-IR Promotes diabetic kidney injury in db/db mice by targeting miR-29b. Diabetes 67, 731–744 (2018).

  170. 170.

    Bai, X. et al. Long noncoding RNA LINC01619 regulates microRNA-27a/forkhead box protein o1 and endoplasmic reticulum stress-mediated podocyte injury in diabetic nephropathy. Antioxid. Redox Signal. 29, 355–376 (2018).

  171. 171.

    Li, A. et al. LincRNA 1700020I14Rik alleviates cell proliferation and fibrosis in diabetic nephropathy via miR-34a-5p/Sirt1/HIF-1α signaling. Cell Death Dis. 9, 461 (2018).

  172. 172.

    Li, X. et al. Long noncoding RNA MALAT1 regulates renal tubular epithelial pyroptosis by modulated miR-23c targeting of ELAVL1 in diabetic nephropathy. Exp. Cell Res. 350, 327–335 (2017).

  173. 173.

    Wang, X. et al. Aberrant expression of long non-coding RNAs in newly diagnosed type 2 diabetes indicates potential roles in chronic inflammation and insulin resistance. Cell Physiol. Biochem. 43, 2367–2378 (2017).

  174. 174.

    Reddy, M. A. et al. Regulation of inflammatory phenotype in macrophages by a diabetes-induced long noncoding RNA. Diabetes 63, 4249–4261 (2014).

  175. 175.

    Das, S. et al. Diabetes mellitus-induced long noncoding RNA Dnm3os regulates macrophage functions and inflammation via nuclear mechanisms. Arterioscler. Thromb. Vasc. Biol. 38, 1806–1820 (2018).

  176. 176.

    Zhang, H. et al. Deep RNA Sequencing uncovers a repertoire of human macrophage long intergenic noncoding RNAs modulated by macrophage activation and associated with cardiometabolic diseases. J. Am. Heart Assoc. 6, e007431 (2017).

  177. 177.

    Lorenzen, J. M. & Thum, T. Long noncoding RNAs in kidney and cardiovascular diseases. Nat. Rev. Nephrol. 12, 360–373 (2016).

  178. 178.

    Fassett, R. G. et al. Biomarkers in chronic kidney disease: a review. Kidney Int. 80, 806–821 (2011).

  179. 179.

    Husseiny, M. I., 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 9, e94591 (2014).

  180. 180.

    Lehmann-Werman, R. et al. Identification of tissue-specific cell death using methylation patterns of circulating DNA. Proc. Natl Acad. Sci. USA 113, E1826–E1834 (2016).

  181. 181.

    Szeto, C. C. et al. Micro-RNA expression in the urinary sediment of patients with chronic kidney diseases. Dis. Markers 33, 137–144 (2012).

  182. 182.

    Neal, C. S. et al. Circulating microRNA expression is reduced in chronic kidney disease. Nephrol. Dial. Transplant. 26, 3794–3802 (2011).

  183. 183.

    Luk, C. C. et al. Urinary biomarkers for the prediction of reversibility in acute-on-chronic renal failure. Dis. Markers 34, 179–185 (2013).

  184. 184.

    Yang, Y. et al. Urine miRNAs: potential biomarkers for monitoring progression of early stages of diabetic nephropathy. Med. Hypotheses 81, 274–278 (2013).

  185. 185.

    Ichii, O. et al. Altered expression of microRNA miR-146a correlates with the development of chronic renal inflammation. Kidney Int. 81, 280–292 (2012).

  186. 186.

    DiStefano, J. K., Taila, M. & Alvarez, M. L. Emerging roles for miRNAs in the development, diagnosis, and treatment of diabetic nephropathy. Curr. Diab. Rep. 13, 582–591 (2013).

  187. 187.

    Cai, X. et al. Serum microRNAs levels in primary focal segmental glomerulosclerosis. Pediatr. Nephrol. 28, 1797–1801 (2013).

  188. 188.

    Karpman, D., Ståhl, A.-l & Arvidsson, I. Extracellular vesicles in renal disease. Nat. Rev. Nephrol. 13, 545 (2017).

  189. 189.

    Barutta, F. et al. Urinary exosomal micrornas in incipient diabetic nephropathy. PLOS ONE 8, e73798 (2013).

  190. 190.

    Li, K. et al. Advances, challenges, and opportunities in extracellular RNA biology: insights from the NIH exRNA Strategic Workshop. JCI Insight 3, 98942 (2018).

  191. 191.

    Argyropoulos, C. et al. Urinary microRNA profiling in the nephropathy of type 1 diabetes. PLOS ONE 8, e54662 (2013).

  192. 192.

    Higuchi, C. et al. Identification of circulating miR-101, miR-375 and miR-802 as biomarkers for type 2 diabetes. Metabolism 64, 489–497 (2015).

  193. 193.

    Pezzolesi, M. G. et al. Circulating TGF-beta1-regulated miRNAs and the risk of rapid progression to ESRD in type 1 diabetes. Diabetes 64, 3285–3293 (2015).

  194. 194.

    Satake, E. et al. Circulating miRNA profiles associated with hyperglycemia in patients with type 1 diabetes mellitus. Diabetes 67, 1013–1023 (2018).

  195. 195.

    Baker, M. A. et al. Tissue-specific microRNA expression patterns in four types of kidney disease. J. Am. Soc. Nephrol. 28, 2985–2992 (2017).

  196. 196.

    Gao, J., Wang, W., Wang, F. & Guo, C. LncRNA-NR_033515 promotes proliferation, fibrogenesis and epithelial-to-mesenchymal transition by targeting miR-743b-5p in diabetic nephropathy. Biomed. Pharmacother. 106, 543–552 (2018).

  197. 197.

    Arrowsmith, C. H., Bountra, C., Fish, P. V., Lee, K. & Schapira, M. Epigenetic protein families: a new frontier for drug discovery. Nat. Rev. Drug Discov. 11, 384 (2012).

  198. 198.

    Jones, P. A., Issa, J. P. & Baylin, S. Targeting the cancer epigenome for therapy. Nat. Rev. Genet. 17, 630–641 (2016).

  199. 199.

    Rafehi, H. et al. Systems approach to the pharmacological actions of HDAC inhibitors reveals EP300 activities and convergent mechanisms of regulation in diabetes. Epigenetics 12, 991–1003 (2017).

  200. 200.

    Advani, A. et al. Long-term administration of the histone deacetylase inhibitor vorinostat attenuates renal injury in experimental diabetes through an endothelial nitric oxide synthase-dependent mechanism. Am. J. Pathol. 178, 2205–2214 (2011).

  201. 201.

    Huang, K. et al. Sirt1 resists advanced glycation end products-induced expressions of fibronectin and TGF-beta1 by activating the Nrf2/ARE pathway in glomerular mesangial cells. Free Radic. Biol. Med. 65, 528–540 (2013).

  202. 202.

    Hong, Q. et al. Increased podocyte Sirtuin-1 function attenuates diabetic kidney injury. Kidney Int. 93, 1330–1343 (2018).

  203. 203.

    Zhou, X. et al. Enhancer of zeste homolog 2 inhibition attenuates renal fibrosis by maintaining smad7 and phosphatase and tensin homolog expression. J. Am. Soc. Nephrol. 27, 2092–2108 (2016).

  204. 204.

    Zhou, X. et al. Targeting histone methyltransferase enhancer of zeste homolog-2 inhibits renal epithelial-mesenchymal transition and attenuates renal fibrosis. FASEB J. 32, 5976–5989 (2018).

  205. 205.

    Lindow, M. & Kauppinen, S. Discovering the first microRNA-targeted drug. J. Cell Biol. 199, 407–412 (2012).

  206. 206.

    Krutzfeldt, J. et al. Silencing of microRNAs in vivo with ‘antagomirs’. Nature 438, 685–689 (2005).

  207. 207.

    Kato, M. et al. A microRNA circuit mediates transforming growth factor-beta1 autoregulation in renal glomerular mesangial cells. Kidney Int. 80, 358–368 (2011).

  208. 208.

    Zhong, X. et al. miR-21 is a key therapeutic target for renal injury in a mouse model of type 2 diabetes. Diabetologia 56, 663–674 (2013).

  209. 209.

    Chau, B. N. et al. MicroRNA-21 promotes fibrosis of the kidney by silencing metabolic pathways. Sci. Transl Med. 4, 121ra18 (2012).

  210. 210.

    Kölling, M. et al. Therapeutic miR-21 silencing ameliorates diabetic kidney disease in mice. Mol. Ther. 25, 165–180 (2017).

  211. 211.

    Dey, N. et al. MicroRNA-21 orchestrates high glucose-induced signals to TOR complex 1, resulting in renal cell pathology in diabetes. J. Biol. Chem. 286, 25586–25603 (2011).

  212. 212.

    Long, J., Wang, Y., Wang, W., Chang, B. H. & Danesh, F. R. MicroRNA-29c is a signature microRNA under high glucose conditions that targets Sprouty homolog 1, and its in vivo knockdown prevents progression of diabetic nephropathy. J. Biol. Chem. 286, 11837–11848 (2011).

  213. 213.

    Dowdy, S. F. Overcoming cellular barriers for RNA therapeutics. Nat. Biotechnol. 35, 222 (2017).

  214. 214.

    Crooke, S. T., Witztum, J. L., Bennett, C. F. & Baker, B. F. RNA-targeted therapeutics. Cell Metab. 27, 714–739 (2018).

  215. 215.

    Rupaimoole, R. & Slack, F. J. MicroRNA therapeutics: towards a new era for the management of cancer and other diseases. Nat. Rev. Drug Discov. 16, 203–222 (2017).

  216. 216.

    Zhou, J. & Rossi, J. Aptamers as targeted therapeutics: current potential and challenges. Nat. Rev. Drug Discov. 16, 181 (2016).

  217. 217.

    Doudna, J. A. & Charpentier, E. The new frontier of genome engineering with CRISPR-Cas9. Science 346, 1258096 (2014).

  218. 218.

    Dominguez, A. A., Lim, W. A. & Qi, L. S. Beyond editing: repurposing CRISPR–Cas9 for precision genome regulation and interrogation. Nat. Rev. Mol. Cell Biol. 17, 5 (2015).

  219. 219.

    Liao, H.-K. et al. In vivo target gene activation via CRISPR/Cas9-mediated trans-epigenetic modulation. Cell 171, 1–13 (2017).

  220. 220.

    Komor, A. C., Badran, A. H. & Liu, D. R. CRISPR-based technologies for the manipulation of eukaryotic genomes. Cell 168, 20–36 (2017).

  221. 221.

    Nishida, K. et al. Targeted nucleotide editing using hybrid prokaryotic and vertebrate adaptive immune systems. Science 353, aaf8729 (2016).

  222. 222.

    Kim, Y. B. et al. Increasing the genome-targeting scope and precision of base editing with engineered Cas9-cytidine deaminase fusions. Nat. Biotechnol. 35, 371 (2017).

  223. 223.

    Gaudelli, N. M. et al. Programmable base editing of A·T to G·C in genomic DNA without DNA cleavage. Nature 551, 464 (2017).

  224. 224.

    Mali, P. et al. CAS9 transcriptional activators for target specificity screening and paired nickases for cooperative genome engineering. Nat. Biotechnol. 31, 833 (2013).

  225. 225.

    Gilbert, L. A. et al. Genome-scale CRISPR-mediated control of gene repression and activation. Cell 159, 647–661 (2014).

  226. 226.

    Kearns, N. A. et al. Functional annotation of native enhancers with a Cas9–histone demethylase fusion. Nat. Methods 12, 401 (2015).

  227. 227.

    Liu, X. S. et al. Editing DNA methylation in the mammalian genome. Cell 167, 233–247 (2016).

  228. 228.

    Hilton, I. B. et al. Epigenome editing by a CRISPR-Cas9-based acetyltransferase activates genes from promoters and enhancers. Nat. Biotechnol. 33, 510 (2015).

  229. 229.

    Verma, N. et al. TET proteins safeguard bivalent promoters from de novo methylation in human embryonic stem cells. Nat. Genet. 50, 83–95 (2018).

  230. 230.

    Morita, S. et al. Targeted DNA demethylation in vivo using dCas9–peptide repeat and scFv–TET1 catalytic domain fusions. Nat. Biotechnol. 34, 1060 (2016).

  231. 231.

    WareJoncas, Z. et al. Precision gene editing technology and applications in nephrology. Nat. Rev. Nephrol. 14, 663–677 (2018).

  232. 232.

    Cardenas, A. et al. Validation of a DNA methylation reference panel for the estimation of nucleated cells types in cord blood. Epigenetics 11, 773–779 (2016).

Download references


The authors gratefully acknowledge funding from the US National Institutes of Health (National Institute of Diabetes and Digestive and Kidney Diseases and National Heart, Lung, and Blood Institute), the Wanek Family Project to Cure Type 1 Diabetes at City of Hope and the Juvenile Diabetes Research Foundation. The authors thank S. T. Wilkinson and K. Higa (Office of Faculty and Institutional Support, Beckman Research Institute of City of Hope) for help editing the manuscript before submission.

Author information


  1. Department of Diabetes Complications and Metabolism, Diabetes Metabolism Research Institute, Beckman Research Institute of City of Hope, Duarte, CA, USA

    • Mitsuo Kato
    •  & Rama Natarajan


  1. Search for Mitsuo Kato in:

  2. Search for Rama Natarajan in:


Both authors contributed to researching data for the article, discussing the article’s content, writing the article and reviewing and editing the manuscript before submission.

Competing interests

The authors declare no competing interests.

Corresponding authors

Correspondence to Mitsuo Kato or Rama Natarajan.


Non-coding RNAs

(ncRNAs). An RNA molecule that is not translated into protein; ncRNAs can regulate gene expression at the transcriptional and post-transcriptional levels.

Genome-wide association studies

(GWAS). Cataloguing of genetic variants across the genomes of multiple individuals that are associated with a specific phenotype.


Short (50–1,500 bp) regions of DNA that can be bound by transcriptional activators to increase the transcription of a particular gene. An enhancer may be located upstream or downstream of the gene it regulates and does not have to be close to the transcription initiation site.

DNA methylation

An epigenetic modification that adds a methyl (CH3) group to DNA, typically at the 5′-cytosine (C) of CpG dinucleotides.

Histone post-translational modifications

(PTMs). Covalent modifications (for example, methylation, phosphorylation and acetylation) on histone residues that facilitate epigenetic regulation of gene expression by altering chromatin structure or recruiting chromatin modifiers.

Genomic imprinting

A phenomenon whereby maternal and paternal chromosomes (or genes) are differentially marked and either maternal or paternal genes are selectively suppressed. DNA methylation is a key mark for genomic imprinting.


A process of copying DNA into the growing RNA chain by RNA polymerase during the elongation phase of transcription.

Alternative splicing

A process that allows multiple mRNAs to be transcribed from a single gene. Usually, certain exons of a gene are included or excluded from the final processed mRNA.

Histone deacetylase

(HDAC). Enzyme that removes the acetyl group from histones.

Epigenome-wide association studies

(EWAS). Cataloguing of epigenetic marks (typically focused on DNA methylation) across the genomes of multiple individuals that are associated with a specific phenotype.


(Encyclopedia of DNA Elements). A public research consortium funded by the National Human Genome Research Institute to systematically identify all functional elements in the human and mouse genomes.

Methylated DNA immunoprecipitation sequencing

(Me-DIP-seq). A method to identify the profile of genome-wide DNA methylation by sequencing DNA immunoprecipitated with antibody to 5-methylcytosine (5mC).

Reduced representation bisulfite sequencing

(RRBS-seq). A technique for analysing the genome-wide DNA methylation profiles with single-nucleotide resolution at relatively low cost. It combines restriction enzyme and bisulfite sequencing to enrich (~1% of genome) for areas of the genome with a high CpG content.

Whole-genome bisulfite sequencing

The gold standard method for the analysis of DNA methylation of single cytosines at base resolution in the whole genome. It involves next-generation sequencing of bisulfite-converted DNA. Sodium bisulfite converts unmethylated cytosine into uracil, which eventually will appear as thymine after sequencing. Methylated cytosines appear as cytosine.


Encompasses a set of epigenetic marks (DNA methylation and histone modifications) unique to specific cells or individuals that determine their cell fate or phenotypes (disease susceptibility), respectively.

Chromatin immunoprecipitation (ChIP) followed by sequencing

(ChIP–seq). A method to analyse protein interactions with DNA. ChIP–seq combines ChIP using specific antibodies to a target protein followed by high-throughput DNA sequencing to identify the binding sites of DNA-associated proteins in a genome-wide fashion.

Mediator complexes

A multiprotein complex that is required for gene transcription by RNA polymerase II and functions as a transcriptional co-activator in eukaryotes. Subunits of the complex relay information from signals and transcription factors to the RNA polymerase II machinery to control the expression of specific genes.

Poised promoters

Promoters that are defined by the simultaneous presence of histone modifications associated with both gene activation and repression (bivalent). They are frequently found at the promoters and enhancers of developmental and lineage-specific genes.


A process of pro-inflammatory programmed cell death that is also a form of regulated necrosis, a lytic type of cell death inherently associated with inflammation.

Foam cells

Lipid-laden macrophages that serve as the hallmark of early-stage atherosclerotic lesion formation.


Cell-derived vesicles that are present in biofluids, including blood, urine, cerebrospinal fluid and conditioned medium of cultured cells. The diameter of exosomes is 30–100 nm.

Locked nucleic acid

(LNA). A modified RNA nucleotide in which the ribose moiety is modified with an extra bridge connecting the 2′ oxygen and 4′ carbon. The bridge ‘locks’ the ribose in the 3′-endo conformation, which is often found in the A-form duplexes. LNA nucleotides are very stable and have high affinity for target DNA or RNA residues, to which they hybridize.


Small synthetic RNAs that are designed to silence endogenous microRNAs.

About this article

Publication history