Abordaje nutrigenómico de la obesidad: ¿dónde estamos?
DOI:
https://doi.org/10.35454/rncm.v4n1.167Palabras clave:
Nutrigenómica, Genética, ObesidadResumen
La obesidad es una enfermedad multifactorial, es decir que resulta de la interacción de múltiples factores genéticos y ambientales. Para su estudio se hace necesario el uso de herramientas de investigación que permitan explorar mecanismos de interacción entre el genoma completo y la nutrición. La genómica nutricional que engloba la nutrigenética y la nutrigenómica ha estudiado el papel de los genes en la obesidad. Aunque estas dos últimas están íntimamente asociadas, toman un enfoque diferente para entender la relación entre los genes y la dieta.
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World Health Organization. Obesity and Overweight [Internet]. 1 April 2020. [Fecha de consulta: 21 de mayo de 2020]. Disponible en: https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight.
Hruby A, Hu FB. The Epidemiology of Obesity: A Big Picture. Pharmacoeconomics. 2015; 33(7): 673–89. doi: https://doi.org/10.1007/s40273-014-0243-x.
Hales CM, Carroll MD, Fryar CD, Ogden CL. Prevalence of Obesity and Severe Obesity Among Adults: United States, 2017–2018 [Internet]. Centers for Disease Control and Prevention (CDC); February 2020. [Fecha de consulta: 21 de mayo de 2020]. Disponible en: https://www.cdc.gov/nchs/products/databriefs/db360.htm.
Organización Panamericana de la Salud, Organización Mundial de la Salud. Sobrepeso Afecta a Casi La Mitad De La Población De Todos Los Países De América Latina y El Caribe Salvo Por Haití [Internet]. Santiago de Chile; 19 de enero de 2017. [Fecha de consulta: 21 de mayo de 2020]. Disponible en: https://www.paho.org/col/index.php?option=com_content&view=article&id=2686:sobrepeso-afecta-a-casi-la-mitad-de-la-poblacion-de-todos-los-paises-de-america-latina-y-el-caribe-salvo-por-haiti&Itemid=562.
Shamah-Levy T, Campos-Nonato I, Cuevas-Nasu L, Hernández-Barrera L, Morales-Ruán MDC, Rivera-Dommarco J, et al. Overweight and obesity in Mexican vulnerable population. Results of Ensanut 100k. Salud Pública Méx. 2019; 61(6): 852-65. doi: https://doi.org/10.21149/10585.
Instituto Colombiano de Bienestar Familiar. ENSIN: Encuesta Nacional De Situación Nutricional 2015. [Fecha de consulta: 21 de mayo de 2020]. Disponible en: https://www.icbf.gov.co/bienestar/nutricion/encuesta-nacional-situacion-nutricional.
Ritchie H, Roser M. Obesity [Internet]. Our world in data. 2017. [Fecha de consulta: 21 de mayo de 2020]. Disponible en: ourworldindata.org/obesity.
Smith KB, Smith MS. Obesity Statistics. Prim Care. 2016;43(1):121–35. doi: https://doi.org/10.1016/j.pop.2015.10.001.
Castillo JJ, Orlando RA, Garver WS. Gene-Nutrient Interactions and Susceptibility to Human Obesity. Genes Nutr. 2017;12:29. doi: https://doi.org/10.1186/s12263-017-0581-3.
Mutch DM, Wahli W, Williams fecon G. Nutrigenomics and nutrigenetics: the emerging faces of nutrition. FASEB J. 2005;19(12):1602-16. doi: https://doi.org/10.1096/fj.05-3911rev.
Phillips CM. Nutrigenetics and Metabolic Disease: Current Status and Implications for Personalised Nutrition. Nutrients. 2013; 5(1): 32-57. doi: https://doi.org/10.3390/nu5010032.
de Toro-Martín J, Arsenault BJ, Després J-P, Vohl M-C. Precision Nutrition: A Review of Personalized Nutritional Approaches for the Prevention and Management of Metabolic Syndrome. Nutrients. 2017; 9(8): 913. doi: https://doi.org/10.3390/nu9080913.
Peña-Romero AC, Navas-Carrillo D, Marín F, Orenes-Piñero E. The future of nutrition: Nutrigenomics and nutrigenetics in obesity and cardiovascular diseases. Crit Rev Food Sci Nutr. 2018;58(17):3030-41. doi: https://doi.org/10.1080/10408398.2017.1349731.
Pertea M, Shumate A, Pertea G, Varabyou A, Breitwieser FP, Chang Y-C, et al. CHESS: a new human gene catalog curated from thousands of large-scale RNA sequencing experiments reveals extensive transcriptional noise. Genome Biol. 2018; 19(1): 208. doi: https://doi.org/10.1186/s13059-018-1590-2.
García-Ortega LF, Martínez O. How Many Genes Are Expressed in a Transcriptome? Estimation and Results for RNA-Seq. PloS one. 2015; 10(6): e0130262. doi: https://doi.org/10.1371/journal.pone.0130262.
Olivier M, Asmis R, Hawkins GA, Howard TD, Cox LA. The Need for Multi-Omics Biomarker Signatures in Precision Medicine. Int J Mol Sci. 2019; 20(19):4781. doi: https://doi.org/10.3390/ijms20194781.
Genomes Project Consortium, Auton A, Brooks LD, Durbin RM, Garrison EP, Kang HM, et al. A global reference for human genetic variation. Nature. 2015; 526(7571):68-74. doi: https://doi.org/10.1038/nature15393.
Pigeyre M, Yazdi FT, Kaur Y, Meyre D. Recent progress in genetics, epigenetics and metagenomics unveils the pathophysiology of human obesity. Clin Sci. 2016; 130(12): 943-86. doi: https://doi.org/10.1042/CS20160136.
Huang T, Hu FB. Gene-environment interactions and obesity: recent developments and future directions. BMC Med Genomics. 2015; 8(Suppl 1): S2. doi: https://doi.org/10.1186/1755-8794-8-S1-S2.
Speliotes EK, Willer CJ, Berndt SI, Monda KL, Thorleifsson G, Jackson AU, et al. Association analyses of 249,796 individuals reveal eighteen new loci associated with body mass index. Nat Genet. 2010;42(11):937-48. doi: https://doi.org/10.1038/ng.686.
Hebebrand J, Volckmar A-L, Knoll N, Hinney A. Chipping Away the ‘Missing Heritability’: GIANT Steps Forward in the Molecular Elucidation of Obesity – but Still Lots to Go. Obes Facts. 2010;3(5):294-303. doi: https://doi.org/10.1159/000321537.
Ramos-Lopez O, Milagro FI, Allayee H, Chmurzynska A, Choi MS, Curi R, et al. Guide for Current Nutrigenetic, Nutrigenomic, and Nutriepigenetic Approaches for Precision Nutrition Involving the Prevention and Management of Chronic Diseases Associated with Obesity. J Nutrigenet Nutrigenomics. 2017;10(1-2):43-62. doi: https://doi.org/10.1159/000477729.
Mousavizadeh Z, Hosseini-Esfahani F, Javadi A, Daneshpour MS, Akbarzadeh M, Mirmrian P, et al. The interaction between dietary patterns and melanocortin-4 receptor polymorphisms in relation to obesity phenotypes. Obes Res Clin Pract. 2020;14(3):249-56. doi: https://doi.org/10.1016/j.orcp.2020.04.002
Vázquez-Moreno M, Zeng H, Locia-Morales D, Peralta-Romero J, Asif H, Maharaj A, et al. The Melanocortin 4 Receptor p.Ile269Asn Mutation Is Associated with Childhood and Adult Obesity in Mexicans. J Clin Endocrinol Metab. 2020;105(4): dgz276. doi: https://doi.org/10.1210/clinem/dgz276.
Su X, Peng D. The exchangeable apolipoproteins in lipid metabolism and obesity. Clin Chim Acta. 2020;503:128-35. doi: https://doi.org/10.1016/j.cca.2020.01.015.
Kumar A, Shalimar, Walia GK, Gupta V, Sachdeva MP. Genetics of nonalcoholic fatty liver disease in Asian populations. J Genet. 2019;98:29.
Heianza Y, Qi L. Gene-Diet Interaction and Precision Nutrition in Obesity. Int J Mol Sci. 2017;18(4):787. doi: https://doi.org/10.3390/ijms18040787.
Almond D, Currie J. Killing Me Softly: The Fetal Origins Hypothesis. J Econ Perspect. 2011; 25(3):153-72. doi: https://doi.org/10.1257/jep.25.3.153.
Burdge GC, Hoile SP, Lillycrop KA. Epigenetics: are there implications for personalised nutrition? Curr Opin Clin Nutr Metab Care. 2012; 15(5):442-7. doi: https://doi.org/10.1097/MCO.0b013e3283567dd2.
McCaffery J. Precision behavioral medicine: Implications of genetic and genomic discoveries for behavioral weight loss treatment. Am Psychol. 2018; 73(8):1045-55. doi: https://doi.org/10.1037/amp0000253.
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. doi: https://doi.org/10.1038/nature20784.
Oliver P, Reynés B, Caimari A, Palou A. Peripheral blood mononuclear cells: a potential source of homeostatic imbalance markers associated with obesity development. Pflugers Arch. 2013;465(4):459-68. doi: https://doi.org/10.1007/s00424-013-1246-8.
de Mello FVD, Kolehmanien M, Schwab U, Pulkkinen L, Uusitupa M. Gene expression of peripheral blood mononuclear cells as a tool in dietary intervention studies: What do we know so far? Mol Nutr Food Res. 2012; 56(7):1160-72. doi: https://doi.org/10.1002/mnfr.201100685.
Jang K, Tong T, Lee J, Park T, Lee H. Altered Gene Expression Profiles in Peripheral Blood Mononuclear Cells in Obese Subjects. Obes Facts. 2020;13(3): 375-85. doi: https://doi.org/10.1159/000507817.
Sanchez J, Pico C, Ahrens W, Foraita R, Fraterman A, Moreno LA, et al. Transcriptome analysis in blood cells from children reveals potential early biomarkers of metabolic alterations. Int J Obes. 2017; 41(10):1481-8. doi : https://doi.org/10.1038/ijo.2017.132.
Takamura T, Honda M, Sakai Y, Ando H, Shimizu A, Ota T, et al. Gene expression profiles in peripheral blood mononuclear cells reflect the pathophysiology of type 2 diabetes. Biochem Biophys Res Commun. 2007; 361(2): 379-84. doi: https://doi.org/10.1016/j.bbrc.2007.07.006.
Ortiz-Dosal A, Rodil-Garcia P, Salazar-Olivo LA. Circulating microRNAs in human obesity: a systematic review. Biomarkers. 2019; 24(6): 499-509. doi: https://doi.org/10.1080/1354750X.2019.1606279.
Langi G, Szczerbinski L, Kretowski A. Meta-Analysis of Differential miRNA Expression after Bariatric Surgery. J Clin Med. 2019;8(8):1220. doi: https://doi.org/10.3390/jcm8081220.
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Derechos de autor 2020 Julian López Rippe
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0.