Skip to main content Accessibility help
×
Home

Twin studies advance the understanding of gene–environment interplay in human nutrigenomics

  • Tess Pallister (a1), Tim D. Spector (a1) and Cristina Menni (a1)

Abstract

Investigations into the genetic architecture of diet–disease relationships are particularly relevant today with the global epidemic of obesity and chronic disease. Twin studies have demonstrated that genetic makeup plays a significant role in a multitude of dietary phenotypes such as energy and macronutrient intakes, dietary patterns, and specific food group intakes. Besides estimating heritability of dietary assessment, twins provide a naturally unique, case–control experiment. Due to their shared upbringing, matched genes and sex (in the case of monozygotic (MZ) twin pairs), and age, twins provide many advantages over classic epidemiological approaches. Future genetic epidemiological studies could benefit from the twin approach particularly where defining what is ‘normal’ is problematic due to the high inter-individual variability underlying metabolism. Here, we discuss the use of twins to generate heritability estimates of food intake phenotypes. We then highlight the value of discordant MZ pairs to further nutrition research through discovery and validation of biomarkers of intake and health status in collaboration with cutting-edge omics technologies.

  • View HTML
    • Send article to Kindle

      To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

      Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

      Find out more about the Kindle Personal Document Service.

      Twin studies advance the understanding of gene–environment interplay in human nutrigenomics
      Available formats
      ×

      Send article to Dropbox

      To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

      Twin studies advance the understanding of gene–environment interplay in human nutrigenomics
      Available formats
      ×

      Send article to Google Drive

      To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

      Twin studies advance the understanding of gene–environment interplay in human nutrigenomics
      Available formats
      ×

Copyright

Corresponding author

* Corresponding author: Tim D. Spector, fax +44 20 7188 6761, email tim.spector@kcl.ac.uk

References

Hide All
1 Brown, JE & Carlson, M (2000) Nutrition and multifetal pregnancy. J Am Diet Assoc 100, 343348.
2 Rankinen, T & Bouchard, C (2006) Genetics of food intake and eating behavior phenotypes in humans. Annu Rev Nutr 26, 413434.
3 Kussmann, M, Raymond, F & Affolter, M (2006) OMICS-driven biomarker discovery in nutrition and health. J Biotechnol 124, 758787.
4 Zivkovic, AM & German, JB (2009) Metabolomics for assessment of nutritional status. Current Opin Clin Nutr Metab Care 12, 501507.
5 Visscher, PM, Hill, WG & Wray, NR (2008) Heritability in the genomics era – concepts and misconceptions. Nat Rev Genet 9, 255266.
6 de Castro, JM (1993) Genetic influences on daily intake and meal patterns of humans. Physiol Behav 53, 777782.
7 Guyenet, SJ & Schwartz, MW (2012) Clinical review: regulation of food intake, energy balance, and body fat mass: implications for the pathogenesis and treatment of obesity. J Clin Endocrinol Metab 97, 745755.
8 Liu, J, Tuvblad, C, Raine, A, et al. (2013) Genetic and environmental influences on nutrient intake. Genes Nutr 8, 241252.
9 Pimpin, L, Ambrosini, GL, Llewellyn, CH, et al. (2013) Dietary intake of young twins: nature or nurture? Am J Clin Nutr 98, 13261334.
10 Heller, RF, O'Connell, DL, Roberts, DC, et al. (1988) Lifestyle factors in monozygotic and dizygotic twins. Genet Epidemiol 5, 311321.
11 Wade, J, Milner, J & Krondl, M (1981) Evidence for a physiological regulation of food selection and nutrient intake in twins. Am J Clin Nutr 34, 143147.
12 Hasselbalch, AL, Heitmann, BL, Kyvik, KO, et al. (2008) Studies of twins indicate that genetics influence dietary intake. J Nutr 138, 24062412.
13 Aden, DP, Fogel, A, Plotkin, S, et al. (1979) Controlled synthesis of HBsAg in a differentiated human liver carcinoma-derived cell line. Nature 282, 615616.
14 Hur, YM, Bouchard, TJ Jr & Eckert, E (1998) Genetic and environmental influences on self-reported diet: a reared-apart twin study. Physiol Behav 64, 629636.
15 Dubois, L, Ohm Kyvik, K, Girard, M, et al. (2012) Genetic and environmental contributions to weight, height, and BMI from birth to 19 years of age: an international study of over 12,000 twin pairs. PLOS ONE 7, e30153.
16 Llewellyn, CH, Trzaskowski, M, Plomin, R, et al. (2014) From modeling to measurement: developmental trends in genetic influence on adiposity in childhood. Obesity (Silver Spring) 22, 17561761.
17 de Castro, JM (1993) Independence of genetic influences on body size, daily intake, and meal patterns of humans. Physiol Behav 54, 633639.
18 Faith, MS, Rha, SS, Neale, MC, et al. (1999) Evidence for genetic influences on human energy intake: results from a twin study using measured observations. Behav Genet 29, 145154.
19 de Castro, JM (2006) Heredity influences the dietary energy density of free-living humans. Physiol Behav 87, 192198.
20 Hu, FB (2002) Dietary pattern analysis: a new direction in nutritional epidemiology. Curr Opin Lipidol 13, 39.
21 Breen, FM, Plomin, R & Wardle, J (2006) Heritability of food preferences in young children. Physiol Behav 88, 443447.
22 Faith, MS, Rhea, SA, Corley, RP, et al. (2008) Genetic and shared environmental influences on children's 24-h food and beverage intake: sex differences at age 7 y. Am J Clin Nutr 87, 903911.
23 Wardle, J, Sanderson, S, Gibson, EL, et al. (2001) Factor-analytic structure of food preferences in four-year-old children in the UK. Appetite 37, 217223.
24 Cooke, LJ, Haworth, CM & Wardle, J (2007) Genetic and environmental influences on children's food neophobia. Am J Clin Nutr 86, 428433.
25 van den Berg, L, Henneman, P, Willems van Dijk, K, et al. (2013) Heritability of dietary food intake patterns. Acta Diabetol 50, 721726.
26 Keskitalo, K, Silventoinen, K, Tuorila, H, et al. (2008) Genetic and environmental contributions to food use patterns of young adult twins. Physiol Behav 93, 235242.
27 Teucher, B, Skinner, J, Skidmore, PM, et al. (2007) Dietary patterns and heritability of food choice in a UK female twin cohort. Twin Res Hum Genet 10, 734748.
28 Gunderson, EP, Tsai, AL, Selby, JV, et al. (2006) Twins of mistaken zygosity (TOMZ): evidence for genetic contributions to dietary patterns and physiologic traits. Twin Res Hum Genet 9, 540549.
29 van den Bree, MB, Eaves, LJ & Dwyer, JT (1999) Genetic and environmental influences on eating patterns of twins aged >/ = 50 y. Am J Clin Nutr 70, 456465.
30 Scarr, S (1968) Environmental bias in twin studies. Eugen Q 15, 3440.
31 Breslin, PA (2013) An evolutionary perspective on food and human taste. Curr Biol 23, R409R418.
32 Fildes, A, van Jaarsveld, CH, Llewellyn, CH, et al. (2014) Nature and nurture in children's food preferences. Am J Clin Nutr 99, 911917.
33 McGue, M & Bouchard, TJ Jr (1984) Adjustment of twin data for the effects of age and sex. Behav Genet 14, 325343.
34 de Castro, JM (1993) A twin study of genetic and environmental influences on the intake of fluids and beverages. Physiol Behav 54, 677687.
35 Agrawal, A & Lynskey, MT (2008) Are there genetic influences on addiction: evidence from family, adoption and twin studies. Addiction 103, 10691081.
36 Yang, A, Palmer, AA & de Wit, H (2010) Genetics of caffeine consumption and responses to caffeine. Psychopharmacology 211, 245257.
37 Feeney, E, O'Brien, S, Scannell, A, et al. (2011) Genetic variation in taste perception: does it have a role in healthy eating? Proc Nutr Soc 70, 135143.
38 Knaapila, A, Hwang, LD, Lysenko, A, et al. (2012) Genetic analysis of chemosensory traits in human twins. Chem Senses 37, 869881.
39 Berge, JM (2009) A review of familial correlates of child and adolescent obesity: what has the 21st century taught us so far? Int J Adolesc Med Health 21, 457483.
40 Anzman-Frasca, S, Savage, JS, Marini, ME, et al. (2012) Repeated exposure and associative conditioning promote preschool children's liking of vegetables. Appetite 58, 543553.
41 Pollard, SL, Zachary, DA, Wingert, K, et al. (2014) Family and community influences on diabetes-related dietary change in a low-income urban neighborhood. Diabetes Educ 40, 462469.
42 Hasselbalch, AL, Angquist, L, Christiansen, L, et al. (2010) A variant in the fat mass and obesity-associated gene (FTO) and variants near the melanocortin-4 receptor gene (MC4R) do not influence dietary intake. J Nutr 140, 831834.
43 Bouchard-Mercier, A, Paradis, AM, Perusse, L, et al. (2012) Associations between polymorphisms in genes involved in fatty acid metabolism and dietary fat intakes. J Nutrigenet Nutrigenomics 5, 112.
44 Yang, J, Benyamin, B, McEvoy, BP, et al. (2010) Common SNPs explain a large proportion of the heritability for human height. Nat Genet 42, 565569.
45 Kho, M, Lee, JE, Song, YM, et al. (2013) Genetic and environmental influences on sodium intake determined by using half-day urine samples: the Healthy Twin Study. Am J Clin Nutr 98, 14101416.
46 van Ommen, B & Stierum, R (2002) Nutrigenomics: exploiting systems biology in the nutrition and health arena. Curr Opin Biotechnol 13, 517521.
47 Després, JP, Moorjani, S, Lupien, PJ, et al. (1992) Genetic aspects of susceptibility to obesity and related dyslipidemias. Mol Cellular Biochem 113, 151169.
48 Gibney, MJ, Walsh, M, Brennan, L, et al. (2005) Metabolomics in human nutrition: opportunities and challenges. Am J Clin Nutr 82, 497503.
49 O'Sullivan, A, Gibney, MJ & Brennan, L (2011) Dietary intake patterns are reflected in metabolomic profiles: potential role in dietary assessment studies. Am J Clin Nutr 93, 314321.
50 Altmaier, E, Kastenmuller, G, Romisch-Margl, W, et al. (2011) Questionnaire-based self-reported nutrition habits associate with serum metabolism as revealed by quantitative targeted metabolomics. Eur J Epidemiol 26, 145156.
51 Guertin, KA, Moore, SC, Sampson, JN, et al. (2014) Metabolomics in nutritional epidemiology: identifying metabolites associated with diet and quantifying their potential to uncover diet-disease relations in populations. Am J Clin Nutr 100, 208217.
52 Suhre, K, Shin, SY, Petersen, AK, et al. (2011) Human metabolic individuality in biomedical and pharmaceutical research. Nature 477, 5460.
53 Menni, C, Zhai, G, Macgregor, A, et al. (2013) Targeted metabolomics profiles are strongly correlated with nutritional patterns in women. Metabolomics 9, 506514.
54 Pietilainen, KH, Sysi-Aho, M, Rissanen, A, et al. (2007) Acquired obesity is associated with changes in the serum lipidomic profile independent of genetic effects – a monozygotic twin study. PloS ONE 2, e218.
55 Yang, LV, Radu, CG, Wang, L, et al. (2005) GI-independent macrophage chemotaxis to lysophosphatidylcholine via the immunoregulatory GPCR G2A. Blood 105, 11271134.
56 Glass, CK & Witztum, JL (2001) Atherosclerosis. the road ahead. Cell 104, 503516.
57 Wallner, S & Schmitz, G (2011) Plasmalogens the neglected regulatory and scavenging lipid species. Chem Phys Lipids 164, 573589.
58 Zulyniak, MA & Mutch, DM (2011) Harnessing metabolomics for nutrition research. Curr Pharm Biotechnol 12, 10051015.
59 Wikoff, WR, Anfora, AT, Liu, J, et al. (2009) Metabolomics analysis reveals large effects of gut microflora on mammalian blood metabolites. Proc Nat Acad Sci U S A 106, 36983703.
60 Nicholson, JK, Holmes, E, Kinross, J, et al. (2012) Host-gut microbiota metabolic interactions. Science 336, 12621267.
61 Ursell, LK, Haiser, HJ, Van Treuren, W, et al. (2014) The intestinal metabolome: an intersection between microbiota and host. Gastroenterology 146, 14701476.
62 Qin, J, Li, R, Raes, J, et al. (2010) A human gut microbial gene catalogue established by metagenomic sequencing. Nature 464, 5965.
63 Collins, MD & Gibson, GR (1999) Probiotics, prebiotics, and synbiotics: approaches for modulating the microbial ecology of the gut. Am J Clin Nutr 69, 1052s1057s.
64 Matijašić, BB, Obermajer, T, Lipoglavšek, L, et al. (2014) Association of dietary type with fecal microbiota in vegetarians and omnivores in Slovenia. Eur J Nutr 53, 10511064.
65 Tims, S, Derom, C, Jonkers, DM, et al. (2013) Microbiota conservation and BMI signatures in adult monozygotic twins. ISME J 7, 707717.
66 Simoes, CD, Maukonen, J, Kaprio, J, et al. (2013) Habitual dietary intake is associated with stool microbiota composition in monozygotic twins. J Nutr 143, 417423.
67 Turnbaugh, PJ & Gordon, JI (2009) The core gut microbiome, energy balance and obesity. J Physiol 587, 41534158.
68 Ridaura, VK, Faith, JJ, Rey, FE, et al. (2013) Gut microbiota from twins discordant for obesity modulate metabolism in mice. Science 341, 1241214.
69 Bell, JT & Spector, TD (2012) DNA methylation studies using twins: what are they telling us? Genome Biol 13, 172.
70 Canani, RB, Costanzo, MD, Leone, L, et al. (2011) Epigenetic mechanisms elicited by nutrition in early life. Nutr Res Rev 24, 198205.
71 McKay, JA & Mathers, JC (2011) Diet induced epigenetic changes and their implications for health. Acta Physiol 202, 103118.
72 Zeisel, SH (2009) Epigenetic mechanisms for nutrition determinants of later health outcomes. Am J Clin Nutr 89, 1488s1493s.
73 Loke, YJ, Novakovic, B, Ollikainen, M, et al. (2013) The Peri/postnatal Epigenetic Twins Study (PETS). Twin Res Hum Genet 16, 1320.
74 de Boo, HA & Harding, JE (2006) The developmental origins of adult disease (Barker) hypothesis. Aust N Z J Obstet Gynaecol 46, 414.
75 Fraga, MF, Ballestar, E, Paz, MF, et al. (2005) Epigenetic differences arise during the lifetime of monozygotic twins. Proc Nat Acad Sci U S A 102, 1060410609.
76 Skidmore, PM, Cassidy, A, Swaminathan, R, et al. (2009) An obesogenic postnatal environment is more important than the fetal environment for the development of adult adiposity: a study of female twins. Am J Clin Nutr 90, 401406.
77 Zhao, J, Goldberg, J & Vaccarino, V (2013) Promoter methylation of serotonin transporter gene is associated with obesity measures: a monozygotic twin study. Int J Obes 37, 140145.
78 Souren, NY, Tierling, S, Fryns, JP, et al. (2011) DNA methylation variability at growth-related imprints does not contribute to overweight in monozygotic twins discordant for BMI. Obesity (Silver Spring) 19, 15191522.
79 Lokk, K, Modhukur, V, Rajashekar, B, et al. (2014) DNA methylome profiling of human tissues identifies global and tissue-specific methylation patterns. Genome Biol 15, r54.
80 Dick, KJ, Nelson, CP, Tsaprouni, L, et al. (2014) DNA methylation and body-mass index: a genome-wide analysis. Lancet 383, 19901998.
81 Müller, M & Kersten, S (2003) Nutrigenomics: goals and strategies. Nat Rev Genet 4, 315322.
82 Pietilainen, KH, Naukkarinen, J, Rissanen, A, et al. (2008) Global transcript profiles of fat in monozygotic twins discordant for BMI: pathways behind acquired obesity. PLoS Med 5, e51.
83 Hackl, H, Burkard, TR, Sturn, A, et al. (2005) Molecular processes during fat cell development revealed by gene expression profiling and functional annotation. Genome Biol 6, R108.
84 Keller, H, Dreyer, C, Medin, J, et al. (1993) Fatty acids and retinoids control lipid metabolism through activation of peroxisome proliferator-activated receptor-retinoid X receptor heterodimers. Proc Nat Acad Sci U S A 90, 21602164.
85 Daniele, G, Guardado Mendoza, R, Winnier, D, et al. (2014) The inflammatory status score including IL-6, TNF-α, osteopontin, fractalkine, MCP-1 and adiponectin underlies whole-body insulin resistance and hyperglycemia in type 2 diabetes mellitus. Acta Diabetol 51, 123131.
86 Lander, ES, Linton, LM, Birren, B, et al. (2001) Initial sequencing and analysis of the human genome. Nature 409, 860921.
87 Kussmann, M, Affolter, M & Fay, LB (2005) Proteomics in nutrition and health. Comb Chem High Throughput Screen 8, 679696.
88 Kato, BS, Nicholson, G, Neiman, M, et al. (2011) Variance decomposition of protein profiles from antibody arrays using a longitudinal twin model. Proteome Sci 9, 73.
89 Norheim, F, Gjelstad, IM, Hjorth, M, et al. (2012) Molecular nutrition research: the modern way of performing nutritional science. Nutrients 4, 18981944.
90 MacLellan, WR, Wang, Y & Lusis, AJ (2012) Systems-based approaches to cardiovascular disease. Nat Rev Cardiol 9, 172184.
91 Eady, JJ, Wortley, GM, Wormstone, YM, et al. (2005) Variation in gene expression profiles of peripheral blood mononuclear cells from healthy volunteers. Physiol Genomics 22, 402411.
92 van Dongen, J, Slagboom, PE, Draisma, HH, et al. (2012) The continuing value of twin studies in the omics era. Nat Rev Genet 13, 640653.
93 van Ommen, B, Bouwman, J, Dragsted, LO, et al. (2010) Challenges of molecular nutrition research 6: the nutritional phenotype database to store, share and evaluate nutritional systems biology studies. Genes Nutr 5, 189203.
94 Tucker, KL, Smith, CE, Lai, CQ, et al. (2013) Quantifying diet for nutrigenomic studies. Annu Rev Nutr 33, 349371.
95 Lloyd, AJ, Beckmann, M, Haldar, S, et al. (2013) Data-driven strategy for the discovery of potential urinary biomarkers of habitual dietary exposure. Am J Clin Nutr 97, 377389.
96 Vernocchi, P, Vannini, L, Gottardi, D, et al. (2012) Integration of datasets from different analytical techniques to assess the impact of nutrition on human metabolome. Front Cell Infect Microbiol 2, 156.

Keywords

Related content

Powered by UNSILO
Type Description Title
PDF
Supplementary materials

Pallister Supplementary Material
Tables 1-4

 PDF (423 KB)
423 KB

Twin studies advance the understanding of gene–environment interplay in human nutrigenomics

  • Tess Pallister (a1), Tim D. Spector (a1) and Cristina Menni (a1)

Metrics

Altmetric attention score

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed.