Aportes trasnacionales de la Epigenética a la Prevención de la DM2

A diferencia de la poca información útil para la práctica clínica obtenida de los estudios de genómica para predecir e identificar individuos en riesgo de presentar DM2 (84,85), el aparecimiento de marcadores epigenéticos como los patrones de metilación en promotores genéticos específicos, si pueden ser útiles en la identificación de sujetos y poblaciones con aumentada sensibilidad a presentar DM2 en la vida adulta a causa de factores adversos en la nutrición intrauterina (86).

La identificación de estas poblaciones o individuos, puede ser de gran utilidad para el desarrollo de programas preventivos de DM2, ya sea a través de modificaciones en los estilos de vida o a través de intervenciones nutricionales o farmacológicas activas (87-89). Las consecuencias fenotípicas y epigenéticas del retardo de crecimiento intrauterino en el desarrollo pancreático y el riesgo de presentar DM2 en la vida adulta, podría ser revertidas por intervenciones farmacológicas que modifiquen las alteraciones epigenéticas, así por ejemplo, con medicamentos de uso oncológico como el inhibidor de la deacetilasa de histonas (89).

En conclusión el proceso de transición de individuos nacidos de madres mal nutridas con bajo peso y que en la vida adulta se exponen en hábitos de vida que le conducen a obesidad abdominal, parece ser el determinante de la epidemia de diabetes que se presenta actualmente en los países latinoamericanos.

La comprensión de estos procesos a través de investigaciones epidemiológicas, clínicas y básicas, debe ser una prioridad en nuestra región, y de cuyos resultados dependerán la implementación de programas preventivos eficaces y eficientes que tomen en consideren las diferencias regionales dependientes de mecanismos epigenéticos.

Referencia 

1. King H, Aubert RE, Herman WH. Global burden of diabetes, 1995-2025: prevalence, numerical estimates, and projections. Diabetes Care 1998; 21(9):1414-31.
2. Hogan P, Dall T, Nikolow P. Economic costs of diabetes in the USA in 2002. Diabetes Care 2003; 26(3):917-32.
3. Lopez-Jaramillo P, Pradilla LP, Castillo VR, Lahera V. Socioeconomical pathology as determinant of regional differences in the prevalence of metabolic syndrome and pregnancy-induced hypertension. Rev Esp Cardiol. 2007; 60(2):168-78.
4. Lopez-Jaramillo P, Casas JP, Bautista L, Serrano NC, Morillo CA. An integrated proposal to explain the epidemic of cardiovascular disease in a developing country: From socioeconomic factors to free radicals. Cardiology. 2001; 96(1):1-6.
5. Ministerio de la Protección Social. República de Colombia. Encuesta Nacional de Salud 2007. Hallado en: www.minproteccionsocial.gov.co/ ,14 de febrero del 2010.
6. Manzur F, Alvear C, Alayón A. Caracterización fenotípica y metabólica del síndrome metabólico en Cartagena de Indias. Rev Colomb Cardiol 2008; 15(3): 97-101.
7. Sánchez F, Jaramillo N, Vanegas A, Echeverria JG, Léon AC, Echeverria E, et al. Prevalencia y comportamiento de los factores de riesgo del síndrome metabólico según los diferentes intervalos de edad, en una población femenina del área de influencia de la Clínica de Las Américas, en Medellín-Colombia. Rev Colomb Cardiol 2008; 15(3):102-10.
8. Lombo B, Villalobos C, Tique C, Satizabal C, Franco C. Prevalencia del síndrome metabólico entre los pacientes que asisten al servicio de la clínica de hipertensión de la Fundación Santa Fe de Bogota. Rev Colomb Cardiol 2006; 12(6):472-8.
9. Boyd R, Leigh B, Stuart P. Capillary versus venous bedside blood glucose estimations. Emerg Med J.2005; 22(3):177-9.
10. Sikaris K. The Correlation of Hemoglobin A1c to Blood Glucose. J Diabetes Sci Technol. 2009; 3(3):429-38.
11. Kruijshoop M, Feskens EJ, Blaak EE, de Bruin TW. Validation of capillary glucose measurements to detect glucose intolerance or type 2 diabetes mellitus in the general population. Clin Chim Acta. 2004; 341(1-2):33-40.
12. Hales CN, Barker DJ, Clark PM, Cox LJ, Fall C, Osmond C, et al. Fetal and infant growth and impaired glucose tolerance at age 64. BMJ 1991: 303(6809):1019-22.
13. Hales CN & Barker DJ. Type 2 (non-insulin-dependent) diabetes mellitus: the thrifty phenotype hypothesis. Diabetologia 1992; 35(7):595-601.
14. Lopez-Jaramillo P. Defi ning the research priorities to fi ght the burden of cardiovascular diseases in Latin America. J Hypertens 2008; 26(9):1886-9.
15. Lopez-Jaramillo P. Cardiometabolic disease in Latin America: The role of fetal programming in response to maternal malnutrition. Rev Esp Cardiol 2009; 62(6):670-6
16. Barker DJ, Hales CN, FaU CH, Osmoad C, Phipps K, Clark PM. Type 2 (non-insulin-dependent) diabetes mellitus, hypertension and hyperlipidaemia (syndrome X): relation to reduced fetal growth. Diabetologia 1993;36(1):62-7
17. Kuzawa. C. W. Evolution, developmental plasticity and metabolic disease: In Evolution, Health and Disease (Eds. Stearns, S. C. and Koella. J. C.). Oxford University Press, Oxford. 2007 pp 253-264.
18. López-Jaramillo P, Silva SY, Rodríguez Salamanca N, Duran A, Mosquera W, Castillo V. Are Nutrition- Induced Epigenetic Changes the Link Between Socioeconomic Pathology and Cardiovascular Diseases? Am J Ther 2008; 15(4):362-72.
19. Wellcome Trust Case Control Consortium. Genomewide association study of 14.000 cases of seven common diseases and 3,000 shared controls. Nature 2007; 447(7145): 661-78.
20. Whincup PH, Gilg JA, Papacosta O, Seymour C, Miller GJ, Alberti KG, et al. Early evidence of ethnic differences in cardiovascular risk: cross sectional comparison of British South Asían and white children. BMJ 2002; 324(7338):635.
21. McKeigue PM. Metabolic consequences of obesity and body fat pattern: lessons from migrant studies. Ciba Found. Symp. 1996; 201: 54-64.
22. Whincup PH, Nightingale CM, Owen CG, Rudnicka AR, Gibb I, McKay CM, et al. Early Emergence of Ethnic Differences in Type 2 Diabetes Precursors in the UK: The Child Heart and Health Study in England (CHASE Study). PLoS Med. 2010; 7(4): e1000263.
23. Dhandapany PS, Sadayappan S, Xue Y, Powell GT, Rani DS, Nallari P, et al. A common MYBPC3 (cardiac myosin binding protein C) variant associated with cardíomyopathies in South Asia. Nat Genet. 2009; 41(2):187-91.
24. West-Eberhard MJ. Developmental Plasticity and Evolution (Oxford University Press, New York, 2003).
25. Gluckman PD, Hanson MA and Beedle AS. Early life events and their consequences for later disease: a life history and evolutionary perspective. Am J Hum Biol. 2007; 19(1):1-19.
26. Link CL, McKinlay JB. Disparities in the prevalence of diabetes: is it race/ethnicity or socioeconomic status? Results from the Boston Area Community Health (BACH) survey. Ethn Dis. 2009;19(3):288-92.
27. Beard HA, Al Ghatrif M, Samper-Ternent R, Gerst K, Markides KS. Trends in diabetes prevalence and diabetes-related complications in older Mexican Americans from 1993-1994 to 2004-2005. Diabetes Care. 2009; 32(12): 2212-7.
28. Lopez-Jaramillo P, Garcia G, Camacho P.A, Herrera E, Castillo V. Interrelationship between body mass index, C-reactive protein and blood pressure in a Hispanic pediatric population. Am J Hypertens 2008; 21(5): 527-32
29. Goldberg AD, Allis CD, Bernstein E. Epigenetics: a landscape takes shape. Cell 2007; 128(4):635-8.
30. Weber M, Hellmann I, Stadler MB, Ramos L, Pääbo S, Rebhan M, et al. Distribution, silencing potential and evolutionary impact of prometer DNA methylation in the human genome. Nat. Genet. 2007;39(4):457-66.
31. Meissner A, Mikkelsen TS, Gu H, Wernig M, Hanna J, Sivachenko A, et al. Genome-scale DNA methylation maps of pluripotentiand differentiated cells. Nature 2008; 454(7205):766-70.
32. Nightingale KP, O’Neill LP, Turner BM. Histone modifications: signalling receptors and potential elements of a heritable epigenetic code. Curr opin Genet Dev. 2006; 16(2):125-36.
33. Amaral PP, Mattick JS. Noncoding RNA in development. Mamm Genome.2008;19(7-8):454-92.
34. Reik W. Stability and fl exibility of epigenetic gene regulation in mammalian development. Nature 2007; 447(7143):425-32.
35. Ng RK, Dean W, Dawson C, Lucifero D, Madeja Z, Reik W. et al. Epigenetic restriction of embryonic cell lineage fate by methylation of Elf5. Nat Cell Biol 2008;10(11):1280-90.
36. Park JH, Stoffers DA, Nichoils RD, Simmons RA. Development of type 2 diabetes following intrauterine growth retardation in rats is associated with progressive epigenetic silencing of Pdx1. J Clin Invest. 2008;118(6):2316-24.
37. Lal G, Zhang N, van der Touw W, Ding Y, Ju W, Bottinger EP, et al. Epigenetic regulation of Foxp3 expression in regulatory T cells by DNA methylation. J Immunol. 2009;182(1):259-73.
38. Lillycrop KA, Slater-Jefferies JL, Hanson MA, Godfrey KM, Jackson AA, Burdge GC, et al. Induction of altered epigenetic regulation of the hepatic glucocorticoid receptor in the offspring of rats fed a protein restricted diet during pregnancy suggests that reduced DNA methyitransferase-1 expression is involved in impaired DNA methylation and changes in histone modifi cations. Br J Nutr. 2007; 97(6):1064-73.
39. Bogdarina I, Welham S, King PJ, Burns SP, Clark AJ. Epigenetic modifi cation of the renin-angiotensin system in the fetal programming of hypertension. Círc Res. 2007;100(4):520-6.
40. Pham TD, MacLennan NK, Chiu CT, Laksana GS, Hsu JL, Lane RH. Uteroplacental insuffi ciency increases apoptosis and alters p53 gene methylalion in the full-term IUGR rat kidney. Am J Physiol Regul Integr Comp Physiol. 2003; 285(5): R962-70.
41. Fu Q, McKnight RA, Yu X, Wang L, Callaway CW, Lane RH, et al. Uteroplacental insuffi ciency induces site-specifi c changes in histone H3 covalent modification and affects DNA-hístone H3 positioning in day O IUGR rat liver. Physiol Genomícs. 2004; 20(1):108-116.
42. Raychaudhuri N, Raychaudhuri S, Thamotharan M, Devaskar SU. Histone code modifi cations repress glucose transponer 4 expression in the intrauterine growth-restricted offspring. J Biol Chem. 2008;283(20):13611-26.
43. Sinclair KD, Allegrucci C, Singh R, Gardner DS, Sebastian S, Bispham J, et al. DNA methylation, insulin resistance, and blood pressure in offspring determined by maternal periconceptional B vitamin and methionine status. Proc Nat Acad Sci USA. 2007; 104(49):19351-6.
44. Yajnik CS, Deshpande SS, Jackson AA, Refsum H, Rao S, Fisher DJ, et al. Vitamin B and folate concentralions during pregnancy and insulin resistance in the offspring: the Pune maternal nutrition study. Diabetologia.2008; 51(1):29-38.
45. El-Osta A, Brasacchio D, Yao D, Pocai A, Jones PL, Roeder RG et al. Transient high glucose causes persistent epigenetic changes and altered gen expression during subsequent normoglycemia. J Exp Med. 2008;205(10):2409-17.
46. Villeneuve LM, Reddy MA, Lanting LL, Wang M, Meng L, Natarajan R, et al. Epigenetic histone H3 lysine 9 methylation in metabolic memory and infl ammatory phenotype of vascular smooth muscle cells in diabetes. Proc Nati Acad Sci USA. 2008;105(26):9047-52.
47. Ravelli AC, van der Meulen JH, Osmond C, Barker DJ, Bleker OP. Obesity at the age of 50 years in men and women exposed to famine prenatally. Am J Clin Nutr. 1999;70(5):811-6.
48. Painter RC, de Rooij SR, Bossuyt PM, Simmers TA, Osmond C, Barker DJ, et al. Early onset of coronary artery disease after prenatal exposure to Dutch famine. Am J Clin Nutr. 2006;84(2):322-7.
49. de Rooij SR, Painter RC, Roseboom TJ, Phillis DI, Osmond C, Barker DJ, et al. Glucose tolerance at age 59 and the decline of glucose tolerance in comparison with age 50 in people prenatally exposed to the Dutch famine. Diabetologia. 2006:49(4):637-43
50. 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 USA. 2008; 105(44):17046-9.
51. Drake AJ, Walker BR, Seckl JR. Intergenerational consequences of fetal programming by in útero exposure to glucocorticoids in rats. Am J Physiol Regul Integr Comp Physiol. 2005; 288(1): R34-R38.

52. Burdge GC, Slater-Jefferies J, Torrens C, Phillips ES, Hanson MA, Lillycrop KA, et al. Dietary protein restriction of pregnant rats in the F generation induces altered methylation of hepatic gene promoters in the adult male offspring in the F1 and F2 generations. Br J Nutr. 2007; 97(3):435-9.
53. Jimenez-Chillaron JC, Isganaitis E, Charalambous M, Gesta S, Pentinat-Pelegrin T, Faucette RR, et al. Intergenerational transmission of glucose intolerance and obesity by In útero underntrition in mice. Diabetes. 2009; 58(2): 460-8.
54. Painter RC, Osmond C, Gluckman P, Hanson M, Phillips DI, Roseboom TJ, et al. Transgenerational effects of prenatal exposure to the Dutch famine on neonatal adiposity and health in later life. BJOG 115(10):1243-9.
55. Rueda-Clausen C, Silva F, Lopez-Jaramillo P. Epidemic of obesity and overweigh in Latin America and the Caribbean. Int J Cardiol 2008; 125(1):111-2.
56. Hubert HB, FeinleibM, McNamara PM, Castelli WP. Obesity as an independent risk factor for cardiovascular disease: a 26-year follow-up of participants in the Framingham Heart Study. Circulation. 1983; 67(5): 968–77.
57. Yusuf S, Hawken S, Ounpuu S, Bautista L, Franzosi MG, Commerford P, et al. Obesity and the risk of myocardial infarction in 27,000 participants from 52 countries: a case-control study. Lancet. 2005; 366(9497):1640- 9.
58. CNW Group. First Large Scale International Primary Care Study Confi rms a High Waist Circumference is Independentiy Associated with Cardiovascular Disease.Available at: https://www.newswire.ca/ en/ info/about.cgi. Accessed January 16, 2010.
59. Executive Summary of The Third Report of The National Cholesterol Education Program (NCEP) Expert Panel on (Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III)) JAMA. 2001; 285(19):2486-97.
60. Katzmarzyk PT, Janssen I, Ross R, Church TS, Blair SN, et al. The importance of waist circumference in the definition of metabolic syndrome: prospective analyses of mortality in men. Diabetes Care. 2006; 29(2):404-9.
61. Alberti KG, Zimment P, Shaw J. The metabolic syndrome – a new worldwide defi nition. Lancet 2005; 366(9491):1059-62.
62. López-Jaramillo P, Rueda-Clausen CF, Silva FA. The utility of different defi nitions of metabolic syndrome in Andean population. Int J Cardiol. 2007; 116(3):421-2.
63. Misra A, Vikram NK, Gupta R, et al. Waist circumference cut off points and action levels for Asian Indians for identifi cation of abdominal obesity. Int J Obes (Lond)2006;30 (1):106-111.
64. Velasquez-Melendez G, Kac G, Valente JG, Tavares R, Silva CQ, Garcia ES, et al. Evaluation of waist circumference to predict general obesity and arterial hypertension in women in Greater Metropolitan Belo Horizonte, Brazil. Cad Saude Publica. 2002; 18(3):765-71.
65. Berber A, Gómez-Santos R, Fanghänel G, Sánchez- Reyes L, et al. Anthropometric indexes in the prediction of type 2 diabetes mellitus, hypertension and dyslipidaemia in a Mexican population, Int J Obes Relat Metab Disord. 2001;25(12):1794-9.
66. Pérez M, Casas JP, Cubillos-Garzón LA, Serrano NC, Silva F, Morillo CA, et al. Using waist circumference as a screening tool to identify Colombian subjects at cardiovascular risk. Eur J Cardiovasc Prev Rehabil. 2003;10(5):328-35.
67. García RG, Cifuentes AE, Caballero RS, Sanchez L, López-Jaramillo P, et al. A proposal for an appropriate central obesity diagnosis in Latin American population. Int J Cardiol. 2006;110(2):263-4.
68. Ahima RS, Flier JS. Adipose tissue as an endocrine organ. Trends Endocrinol Metab. 2000;11(8):327-32.
69. Fain JN, Madan AK, Hiler ML, Cheema P, Bahouth SW, et al. Comparison of the release of adipokines by adipose tissue, adipose tissue matrix, and adipocytes from visceral and subcutaneous abdominal adipose tissues of obese humans. Endocrinology. 2004; 145(5):2273-82.
70. Fried SK, Bunkin DA, Greenberg AS. Omental and subcutaneous adipose tissues of obese subjects release interleukin-6: depot difference and regulation by gluco-corticoid. J Clin Endocrinol Metab. 1998; 83 (3):847-850.
71. Fontana L, Eagon JC, Trujillo ME, Scherer PE, Klein S. Visceral fat adipokine secretion is associated with systemic infl ammation in obese humans. Diabetes. 2007;56(4):1010-3.
72. Accini L. Sotomayor A, Trujillo F, Barrera JG, Bautista L, López-Jaramillo P. Colombian Study to Assess the Use of Noninvasive Determination of Endothelium-Mediated Vasodilatation (CANDEV). Normal Values and Factors Associated. Endothelium. 2007;8(2):157-66.
73. Ross R. Atherosclerosis, an infl ammatory disease. N Engl J Med.1999; 340(2):115-26.
74. Bogaty P, Poirier P, Simard S, Boyer L, Solymoss S, Dagenais GR, et al. Biological profi les in subjects with recurrent acute coronary events compared with subjects with long-standing stable angina. Circulation. 2001; 103(25):3062-8.
75. Bautista LE, Lopez-Jaramillo P, Vera LM, Casas JP, Otero AP, Guaracao Al. Is Creactive protein an independent risk factor for essential hypertension?. J Hypertens. 2001; 19(5):857-61.
76. Teran E, Escudero C, Moya W, Flores M, Vallance P, Lopez-Jaramillo P. Etevated C-reactive protein and pro-infl ammatory cytokines in Andean women with pre-eclampsia. Int J Gynaecol Obstet. 2001;75(3):243-9.
77. García RG, Celedón J, Sierra-Laguado J, Alarcon MA, Luengas C, Silva F, et al. Raised C reactive protein and impaired fl ow-mediated vasodilation precede the development of preeclampsia. Am J Hypertens. 2007; 20(1):98-103.
78. García RG, Pérez M, Maas R, Schwedhelm E, Böger RH, López-Jaramillo P. Plasma concentrations of asymmetric dimethylarginine (ADMA) in metabolic syndrome. Int J Cardiol 2007; 122(2):176-8.
79. Okosun IS, Liao Y, Rotimi CN, Prewitt TE, Cooper RS. Abdominal adiposity and clustering of multiple metabolic syndrome in white, black and Hispanic americans. Ann Epidemiol. 2000; 10(5):263-70.
80. Chambers JC, Eda S, Bassett P, Karim Y, Thompson SG, Gallimore JR, et al. C-reactive protein, insulin resistance, central obesity, and coronary heart disease risk in Indian Asians from the United Kingdom compared with European whites. Circulation. 2001; 104(2):145-50.
81. Yusuf S, Hawken S, Ounpuu S, Dans T, Avezum A, Lanas F, et al. Effect of potentially modifi able risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. Lancet. 2004;364(9438):937-52.
82. Lanas F, Avezum A, Bautista LE, Diaz R, Luna M, Islam S, et al. Risk factors for acute myocardial infarction in Latin America: the INTER- HEART Latin American study. Circulation. 2007;115(9):1067-74.
83. Kabagambe EK, Baylin A, Campos H. Nonfatal acute myocardial infarction in Costa Rica: modifi able risk factors, population-attributable risks, and adherence to dietary guidelines. Circulation. 2007; 115(9):1075-81.
84. Meigs JB,Shrader P, Sullivan LM, McAteer JB, Fox CS, Dupuis J, et al. Genotype score in addition to common risk factors for prediction of type 2 diabetes. N Engl J Med.2008; 359(21):2208-19.
85. Lyssenko V, Jonsson A, Almgren P, Pulizzi N, Isomaa B, Tuomi T et al. Clinical risk factors, DNA variants and the development of type 2 diabetes. N Eng J Med 2008; 359(21):2220-32.
86. Lillycrop KA, Phillips ES, Jackson AA, Hanson MA, Burdge GC, et al. Dietary protein restriction of pregnant rats induces and folic acid supplementation prevents epigenetic modifi cation of hepatic gene 87. expression in the offspring. J Nutr.2005; 135(6):1382- 6.
88. Vickers MH, Gluckman PD, Coveny AH, Hofman PL, Cutfi eld WS, Gertler A, et al. Neonatal leptin treatment reverses developmental programming. Endocrinology. 2005;146(10):4211-6.
89. Lawlor DA, Smith GD, O’Callaghan, Alati R, Mamun AA, Williams GM, Me al. Epidemiologic evidence for the fetal overnutrilion hypolhesis: fi ndings from the mater-university study of pregnancy and its outcomes. Am J Epidemiol. 2007;165(4):418-24.
90. Waterland RA, Travisano M, Tahiliani KG, Rached MT, Mirza S. Methyl donor supplementation prevents transgenerational ampiifi cation of obesity. Int J Obes (Lond.).2008;32(9):13