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Nutrigenomics in the modern era

  • John C. Mathers (a1)
Abstract

The concept that interactions between nutrition and genetics determine phenotype was established by Garrod at the beginning of the 20th century through his ground-breaking work on inborn errors of metabolism. A century later, the science and technologies involved in sequencing of the human genome stimulated development of the scientific discipline which we now recognise as nutritional genomics (nutrigenomics). Much of the early hype around possible applications of this new science was unhelpful and raised expectations, which have not been realised as quickly as some would have hoped. However, major advances have been made in quantifying the contribution of genetic variation to a wide range of phenotypes and it is now clear that for nutrition-related phenotypes, such as obesity and common complex diseases, the genetic contribution made by SNP alone is often modest. There is much scope for innovative research to understand the roles of less well explored types of genomic structural variation, e.g. copy number variants, and of interactions between genotype and dietary factors, in phenotype determination. New tools and models, including stem cell-based approaches and genome editing, have huge potential to transform mechanistic nutrition research. Finally, the application of nutrigenomics research offers substantial potential to improve public health e.g. through the use of metabolomics approaches to identify novel biomarkers of food intake, which will lead to more objective and robust measures of dietary exposure. In addition, nutrigenomics may have applications in the development of personalised nutrition interventions, which may facilitate larger, more appropriate and sustained changes in eating (and other lifestyle) behaviours and help to reduce health inequalities.

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Corresponding author
Corresponding author: Professor John C. Mathers, fax +44 (0) 191 2081101; email john.mathers@ncl.ac.uk
References
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1. Garrod, AE (1902) The incidence of alkaptonuria: a study in chemical individuality. Lancet 2, 16161620.
2. Fernández-Cañón, JM, Granadino, B, Beltrán-Valero de Bernabé, D et al. (1996) The molecular basis of alkaptonuria. Nat Genet 14, 1924.
3. Roper, JA (1960) Genetic determination of nutritional requirements. Proc Nutr Soc 19, 3945.
4. Peregrin, T (2001) The new frontier of nutrition science: nutrigenomics. J Am Diet Assoc 10, 1036.
5. Astley, SB (2007) An introduction to nutrigenomics developments and trends. Genes Nutr 2, 1113.
6. Frayling, TM, Timpson, NJ, Weedon, MN et al. (2007) A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science 316, 889894.
7. Cecil, JE, Tavendale, R, Watt, P et al. (2008) An obesity-associated FTO gene variant and increased energy intake in children. N Engl J Med 359, 25582566.
8. Livingstone, KM, Celis-Morales, C, Lara, J et al. (2015) Associations between FTO genotype and total energy and macronutrient intake in adults: a systematic review and meta-analysis. Obes Rev 16, 666678.
9. Locke, AE, Kahali, B, Berndt, S et al. (2015) Genetic studies of body mass index yield new insights for obesity biology. Nature 518, 197206.
10. Fu, J, Hofker, M & Wijmenga, C (2015) Apple or pear: size and shape matter. Cell Metab 21, 507508.
11. Shungin, D, Winkler, TW, Croteau-Chonka, DC et al. (2015) New genetic loci link adipose and insulin biology to body fat distribution. Nature 518, 187196.
12. Belsky, DW, Moffitt, TE, Sugden, K et al. (2013) Development and evaluation of a genetic risk score for obesity. Biodemography Soc Biol. 59, 85100.
13. Hunter, DJ (2005) Gene-environment interactions in human diseases. Nat Rev Genet 6, 287298.
14. Thomas, D (2010) Methods for investigating gene-environment interactions in candidate pathway and genome-wide association studies. Ann Rev Public Health 31, 136.
15. Vimaleswaran, KS, Li, S, Zhao, JH et al. (2009) Physical activity attenuates the body mass index-increasing influence of genetic variation in the FTO gene. Am J Clin Nutr 90, 425428.
16. Celis-Morales, C, Marsaux, CF, Livingstone, KM et al. (2016) Physical activity attenuates the effect of the FTO genotype on obesity traits in European adults: the Food4Me study. Obesity (Silver Spring) . 24, 962969.
17. Qi, Q, Chu, AY, Kang, JH et al. (2012) Sugar-sweetened beverages and genetic risk of obesity. N Engl J Med 367, 13871396.
18. Qi, Q, Chu, AY, Kang, JH et al. (2014) Fried food consumption, genetic risk, and body mass index: gene-diet interaction analysis in three US cohort studies. BMJ 348, g1610.
19. Nettleton, JA, Follis, JL, Ngwa, JS et al. (2015) Gene × dietary pattern interactions in obesity: analysis of up to 68 317 adults of European ancestry. Hum Mol Genet 24, 47284738.
20. Collins, FS & Hamburg, MA (2013) First FDA authorization for next-generation sequencer. N Engl J Med 369, 23692371.
21. Lek, M, Karczewski, KJ, Minikel, EV et al. (2016) Analysis of protein-coding genetic variation in 60,706 humans. Nature 536, 285291.
22. Mullally, A & Ritz, J (2007) Beyond HLA: the significance of genomic variation for allogeneic hematopoietic stem cell transplantation. Blood 109, 13551362.
23. Zarrei, M, MacDonald, JR, Merico, D et al. (2015) A copy number variation map of the human genome. Nat Rev Genet 16, 172183.
24. Perry, GH, Dominy, NJ, Claw, KG et al. (2007) Diet and the evolution of human amylase gene copy number variation. Nat Genet 39, 12561260.
25. Falchi, M, El-Sayed Moustafa, JS, Takousis, P et al. (2014) Low copy number of the salivary amylase gene predisposes to obesity. Nat Genet 46, 492497.
26. Mejía-Benítez, MA, Bonnefond, A, Yengo, L et al. (2015) Beneficial effect of a high number of copies of salivary amylase AMY1 gene on obesity risk in Mexican children. Diabetologia 58, 290294.
27. Carpenter, D, Dhar, S, Mitchell, LM et al. (2015) Obesity, starch digestion and amylase: association between copy number variants at human salivary (AMY1) and pancreatic (AMY2) amylase genes. Hum Mol Genet 24, 34723480.
28. Peterson, RE, Maes, HH, Lin, P et al. (2014) On the association of common and rare genetic variation influencing body mass index: a combined SNP and CNV analysis. BMC Genomics 15, 368.
29. Zhang, D, Li, Z, Wang, H et al. (2015) Interactions between obesity-related copy number variants and dietary behaviors in childhood obesity. Nutrients 7, 30543066.
30. Muller, M & Kersten, S (2003) Nutrigenomics: goals and strategies. Nat Rev Genet 4, 315322.
31. Lange, K, Hugenholtz, F, Jonathan, MC et al. (2015) Comparison of the effects of five dietary fibers on mucosal transcriptional profiles, and luminal microbiota composition and SCFA concentrations in murine colon. Mol Nutr Food Res 59, 15901602.
32. Bouwens, M, Grootte Bromhaar, M, Jansen, J et al. (2010) Postprandial dietary lipid-specific effects on human peripheral blood mononuclear cell gene expression profiles. Am J Clin Nutr 91, 208217.
33. Greaves, LC, Nooteboom, M, Elson, JL et al. (2014) Clonal expansion of early to mid-life mitochondrial DNA point mutations drives mitochondrial dysfunction during human ageing. PLoS Genet 10, e1004620.
34. Méplan, C, Johnson, IT, Polley, AC et al. (2016) Transcriptomics and proteomics show that selenium affects inflammation, cytoskeleton, and cancer pathways in human rectal biopsies. FASEB J 30, 28122825.
35. Verma, M, Hontecillas, R, Abedi, V et al. (2016) Modeling-enabled systems nutritional immunology. Front Nut. 3, 5.
36. Louis, P, Hold, GL & Flint, HJ (2014) The gut microbiota, bacterial metabolites and colorectal cancer. Nat Rev Microbiol 12, 661672.
37. Claesson, MJ, Jeffery, IB, Conde, S et al. (2012) Gut microbiota composition correlates with diet and health in the elderly. Nature 488, 178184.
38. Cotillard, A, Kennedy, SP, Kong, LC et al. (2013) Dietary intervention impact on gut microbial gene richness. Nature 500, 585588.
39. Turnbaugh, PJ & Gordon, JI (2009) The core gut microbiome, energy balance and obesity. J Physiol 587, 41534158.
40. Charbonneau, MR, O'Donnell, D, Blanton, LV et al. (2016) Sialylated milk oligosaccharides promote microbiota-dependent growth in models of infant undernutrition. Cell 164, 859871.
41. Bashiardes, S, Thaiss, CA & Elinav, E (2016) It's in the milk: feeding the microbiome to promote infant growth. Cell Metab 23, 393394.
42. Penn, L, Boeing, H, Boushey, CJ et al. (2010) Assessment of dietary intake: NuGO symposium report. Genes Nutr 5, 205213.
43. Favé, G, Beckmann, ME, Draper, JH et al. (2009) Measurement of dietary exposure: a challenging problem which may be overcome thanks to metabolomics? Genes Nutr 4, 135141.
44. Scalbert, A, Brennan, L, Manach, C et al. (2014) The food metabolome: a window over dietary exposure. Am J Clin Nutr 99, 1286–308.
45. Favé, G, Beckmann, M, Lloyd, AJ et al. (2011) Development and validation of a standardized protocol to monitor human dietary exposure by metabolite fingerprinting of urine samples. Metabolomics 7, 469484.
46. Lloyd, AJ, Beckmann, M, Favé, G et al. (2011) Proline betaine and its biotransformation products in fasting urine samples are potential biomarkers of habitual citrus fruit consumption. Br J Nutr 106, 812824.
47. Lloyd, AJ, Favé, G, Beckmann, M et al. (2011) Use of mass spectrometry fingerprinting to identify urinary metabolites after consumption of specific foods. Am J Clin Nutr 94, 981991.
48. Beckmann, M, Lloyd, AJ, Haldar, S et al. (2013) Dietary exposure biomarker-lead discovery based on metabolomics analysis of urine samples. Proc Nutr Soc. 72, 352361.
49. Beckmann, M, Joosen, AM, Clarke, MM et al. (2016) Changes in the human plasma and urinary metabolome associated with acute dietary exposure to sucrose and the identification of potential biomarkers of sucrose intake. Mol Nutr Food Res 60, 444457.
50. Lara, J, Hobbs, N, Moynihan, PJ et al. (2014) Effectiveness of dietary interventions among adults of retirement age: a systematic review and meta-analysis of randomized controlled trials. BMC Med 12, 60.
51. Celis-Morales, C, Lara, J & Mathers, JC (2015) Personalising nutritional guidance for more effective behaviour change. Proc Nutr Soc 74, 130138.
52. Joost, HG, Gibney, MJ, Cashman, KD et al. (2007) Personalised nutrition: status and perspectives. Br J Nutr. 98, 2631.
53. Nielsen, DE & El-Sohemy, A (2014) Disclosure of genetic information and change in dietary intake: a randomized controlled trial. PLoS ONE 9, e112665.
54. Celis-Morales, C, Livingstone, KM, Marsaux, CF et al. (2015) Design and baseline characteristics of the Food4Me study: a web-based randomised controlled trial of personalised nutrition in seven European countries. Genes Nutr 10, 450.
55. Celis-Morales, C, Livingstone, KM, Marsaux, CF et al. (2016) Effect of personalized nutrition on health-related behaviour change: evidence from the Food4me European randomized controlled trial. Int J Epidemiol (Epublication ahead of print version).
56. Celis-Morales, C, Livingstone, KM, Woolhead, C et al. (2016) How reliable is internet-based self-reported identity, socio-demographic and obesity measures in European adults? Genes Nutr 10, 476.
57. Hoeller, U, Baur, M, Roos, FF et al. (2016) Application of dried blood spots to determine vitamin D status in a large nutritional study with unsupervised sampling: the Food4Me project. Br J Nutr 115, 202211.
58. McKay, JA & Mathers, JC (2016) Maternal folate deficiency and metabolic dysfunction in offspring. Proc Nutr Soc 75, 9095.
59. Lajtha, LG (1979) Stem cell concepts. Differentiation 14, 2334.
60. Keller, G (2005) Embryonic stem cell differentiation: emergence of a new era in biology and medicine. Genes & Dev 19, 11291155.
61. Snykers, S, De Kock, J, Rogiers, V et al. (2009) In vitro differentiation of embryonic and adult stem cells into hepatocytes: state of the art. Stem Cells 27, 577605.
62.The Nobel Prize in Physiology or Medicine 2012 was awarded to Sir John B. Gurdon and Shinya Yamanaka. http://www.nobelprize.org/nobel_prizes/medicine/laureates/2012/press.html (accessed July 2016).
63. Takahashi, K & Yamanaka, S (2006) Induction of pluripotent stem cells from mouse embryonic and adult fibroblast cultures by defined factors. Cell 126, 663676.
64. Huch, M & Koo, BK (2015) Modeling mouse and human development using organoid cultures. Development 142, 31133125.
65. Sato, T, Vries, RG, Snippert, HJ et al. (2009) Single Lgr5 stem cells build crypt-villus structures in vitro without a mesenchymal niche. Nature 459, 262265.
66. Barker, N, Huch, M, Kujala, P et al. (2010) Lgr5(+ve) stem cells drive self-renewal in the stomach and build long-lived gastric units in vitro. Cell Stem Cell 6, 2536.
67. Lancaster, MA, Renner, M, Martin, CA et al. (2013) Cerebral organoids model human brain development and microcephaly. Nature 501, 373379.
68. Maeder, ML & Gersbach, CA (2016) Genome-editing Technologies for gene and cell therapy. Mol Therapy 24, 430446.
69. Niu, Y, Shen, B, Cui, Y et al. (2014) Generation of gene-modified cynomolgus monkey via Cas9/RNA-mediated gene targeting in one-cell embryos. Cell 156, 836843.
70. Baltimore, D, Berg, P & Botchan, M (2015) Biotechnology. A prudent path forward for genomic engineering and germline gene modification. Science 348, 3638.
71. Callaway, E (2016) Gene-editing research in human embryos gains momentum. Nature 532, 289290.
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Proceedings of the Nutrition Society
  • ISSN: 0029-6651
  • EISSN: 1475-2719
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