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Taste and odour: affect on food choices
Professor Ahmed El-Sohemy, University of Toronto  (a.el.sohemy@utoronto.ca)

Food preferences are influenced by a number of factors such as personal experiences, cultural influence and perceived health benefits. Taste and smell are arguably the most important determinants of whether a food is liked or disliked (1). Individual differences in the perception of bitter, sweet, salty, sour, or umami* may influence dietary habits, which can affect nutritional status and risk of chronic diseases. The sense of smell is also an important determinant of the perception of various flavours, and genetic variability affecting olfaction may influence food preferences.

Taste

Sensitivity to bitter tasting compounds is a genetic trait that has been recognized for more than 70 years, and genetic differences in bitter taste perception may account for individual differences in food preferences. Based on the response to bitter tasting compounds such as phenylthiocarbamide (PTC) or 6-n-propylthiouracil (PROP), individuals can be classified as super-tasters, tasters or non-tasters. The TAS2R receptor gene family is known to encode bitter taste receptors on the surface of the tongue and genetic polymorphisms of TAS2R38 have been associated with marked differences in the perception of PTC and PROP (2). Single nucleotide polymorphisms in other taste receptor genes have recently been identified, but their role in bitter taste perception is not yet known.

Populations have typically displayed bimodality in sensitivity to bitter tasting compounds, with approximately 75% of individuals classified as tasters, and 25% classified as non-tasters. Ethnic differences in taster status have also been demonstrated. The frequency of non-tasters has been reported to be approximately 6-23% in China, 30% among North American Caucasians, and 40% in India. This variability in taster status may explain, in part, some of the inconsistencies among different studies relating diet to risk of chronic disease. A genetic polymorphism of TAS2R50 was recently associated with an increased risk of myocardial infarction suggesting that it may be associated with adverse dietary habits (3). Further studies will be needed to determine whether individuals with different TAS2R50 genotypes have different food preferences and dietary habits.

Many bitter tasting foods also contain antioxidants and various phytochemicals, which may play a role in the prevention of certain chronic diseases. An inverse relationship between bitter compound sensitivity, and acceptance of cruciferous vegetables and tart citrus fruits has been reported in young women. A similar observational study found that young women who were sensitive to bitter compounds had reduced preferences for Brussels sprouts, cabbage, spinach and coffee. Individuals who are more sensitive to bitter tasting compounds may, therefore, consume fewer vegetables. Super-tasters might habitually consume fewer vegetables because of an increased sensitivity to the bitter compounds contained within these vegetables. These individuals may in turn eat more sweets or fatty foods, which have been associated with an increased risk of a variety of chronic diseases. A marginally lower risk of diabetes among women who are non-tasters suggests that these individuals may have been more likely to consume a diet rich in bitter tasting vegetables (4). There is also evidence that tasters and super-tasters may have stronger taste acuity in general, and heightened taste perception which may prevent the over consumption of a variety of foods
.

The bitter receptor gene family consists of over two dozen different members, each with its own unique ability to perceive the different tastes of diverse dietary compounds (5). Sweet flavours are detected by the T1R2 and T1R3 genes. Recently, the PkD1L3 and PKD2L1 genes have been linked to sour taste perception 96). In addition, the OR13G1 olfactory gene has been linked with an increased risk of MI. Genetic variations in these and other taste and odour receptors may also be important determinants of preferences for particular foods. Establishing a genetic basis for food likes or dislikes may help to explain some of the discrepancies among epidemiologic studies relating diet to risk of chronic disease.

 

Odour

Olfactory genes form the largest multi-gene family in humans and consist of approximately 9,000 genes. These genes encode olfactory receptors, which interact with odorant molecules in the nose to initiate a neuronal response that triggers the perception of smell. Humans can recognize approximately 10,000 odours. Because olfaction is strongly linked with flavour perception, odour stimuli may play a major role in food preference, and consequently nutritional and health status. As with the TAS2R50 bitter receptor gene, a single nucleotide polymorphism in the OR13G1 gene has been linked with an increased risk of myocardial infarction. This olfactory receptor gene may play an indirect role in increasing the risk of MI by affecting food preferences that are determined by the sense of smell.

Metabolic Selection

Food selection may also be dictated by metabolic needs; there may be physiological mechanisms that direct individuals to select more protein or fat or carbohydrates, depending upon metabolic needs.  Studies in mice showed that different inbred strains preferred food with fat and no carbohydrate over carbohydrate without fat, and other strains preferred the carbohydrate diet when both diets are available [7]. 

Quantitative trait loci (QTL) analyses (see quantitative trait loci analyses) identified three QTLs for energy intake (Kcal1 and Kcal2), three for macronutrient fat intake preference (Minf1 – Minf3) and three for macronutrient carbohydrate preference intake (Minc1 – Minc3) [8].  This study was the first to identify genetic loci associated with intakes of total energy and macronutrients, and demonstrated that nutrient selection was a complex trait, i.e. one in which multiple genes are involved in the process.  Further analyses focused on a ~ 60 Mbp region containing the chromosome 17 QTL for carbohydrate (Minc1) and total energy (Kcal2) intake, traits associated with the CAST/ Ei mice relative to the C57BL/6J (B6) mice.  A congenic strain containing the CAST/ Ei chromosomal 17 region in an otherwise B6 mouse (named B6.CAST-17) consumed 27% more carbohydrate and 17% more total energy compared to a C57BL/6J littermate with the chromosome 17 region from B6 mice [9].  The data confirmed the effect of the chromosome 17 QTL and the difference in magnitude suggests that one or more genes in the B6 background alter some aspects of carbohydrate selection or metabolism and total energy intake through epistatic or gene-environment interactions. 

The location of the peaks Minc1 (12 cM) and Kcal2 (16 cM) overlapped the position of glyoxalase (Glo1) at 16 cM and the glucagon-like peptide 1 receptor (Glp1r) at 18 cM suggesting they could be candidate genes for producing differences in carbohydrate metabolism and energy intake.  Four polymorphisms were found between B6 and CAST/Ei Glp1r including one in the promoter region and a nonsynonomous variant in the coding region (C416Y), and another synonomous change was found in Glo1 between these strains  Strain specific differences Glp1r expression in hypothalamus and antral stomach were consistent with the differences in macronutrient and energy intake. Glo1 was also upregulated in liver and hypothalamus of homozygous B6.Cast-17 relative to B6 mice.

Since Glo1 and Glpr1 are involved in metabolic pathways in many tissues, regulation of intake of macronutrients and energy may be linked to differences in metabolic flux through carbohydrate and energy metabolic pathways. Since there are 1,138 genes in this 60 Mbp region, it is possible that other genes in this region may also be involved in nutrient selection. Hence, nutrient selection may not be driven solely by molecular pathways limited to the hypothalamus (see reviews in 10 and 11) or through taste and odor receptors [12] although the pathways in these organs are likely to play a role in the complex traits underlying food choice.  Some of these pathways are not limited to regions and tissues of the brain associated with regulating nutrient intake [10].  Since the other QTL involved in macronutrient selection and calorie intake [8] have not been fully characterised, development of QTL-specific congenic strains is likely to provide valuable insights into nutrient intake, and may provide knowledge for designing better controlled studies to explore nutrient selection in humans.  Several chromosomal loci associated with total energy and fat intakes in humans were identified in the HERITAGE Family study by a genome wide linkage scan [13].  Identifying causative genes in these regions in human studies is challenging because power calculations would suggest the need for much larger study populations [14].

References

  1. Tepper B.J. & Ullrich N.V. (2002) Taste, smell, and the genetics of food preferences. Topics in Clinical Nutrition 17(4):1-14
  2. Drayna D. (2005) Human Taste Genetics. Annual review of genomics and human genetics
  3. Shiffman D., Ellis S.G., Rowland C.M., et al. (2005) Identification of four gene variants associated with myocardial infarction. American Journal of Human Genetics 77(4):596-605
  4. Timpson N.J., Christensen M., Lawlor D.A., Gaunt T.R., Day I.N., Davey Smith G. (2005) TAS2R38 (phenylthiocarbamide) haplotypes, coronary heart disease traits, and eating behavior in the British Women's Heart and Health Study. American Journal of Clinical Nutrition 81(5):1005-11
  5. Kim U.K. & Drayna D. (2005) Genetics of individual differences in bitter taste perception: lessons from the PTC gene. Clincal Genetics 67(4):275-80
  6. Ishimaru Y., Inada H., Kubota M., Zhuang H., Tominaga M., Matsunami H. (2006) Transient receptor potential family members PKD1L3 and PKD2L1 form a candidate sour taste receptor. Proceedings of the National Academy of Sciences of the United States of America 103:12569-74
  7. Smith B.K., Andrews P.K. & West D.B. (2000) Macronutrient diet selection in thirteen mouse strains. American Journal of Physiology: Regulatory, Integrative & Comparative Physiology 278(4): R797-805
  8. Smith Richards B.K., Belton B.N., Poole A.C., Mancuso J.J., Churchill G.A., Li R., Volaufova J., Zuberi A., & York, B. (2002) QTL analysis of self-selected macronutrient diet intake: fat, carbohydrate, and total kilocalories. Physiological Genomics 11(3): 205-17
  9. Kumar K.G., Poole A.C., York B., Volaufova J., Zuberi A. & Richards B.K. (2007) Quantitative trait loci for carbohydrate and total energy intake on mouse chromosome 17: congenic strain confirmation and candidate gene analyses (Glo1, Glp1r). American Journal of Physiology: Regulatory, Integrative & Comparative Physiology 292(1): R207-16
  10. Seeley R.J., Drazen D.L. & Clegg D.J. (2004) The critical role of the melanocortin system in the control of energy balance. Annual Reviews of Nutrition 24: 133-149
  11. Sato T., Meguid M.M., Fetissov S.O., Chen C. & Zhang L. (2001) Hypothalamic dopaminergic receptor expressions in anorexia of tumor-bearing rats.  American Journal of Physiology: Regulatory, Integrative & Comparative Physiology 281(6): R1907-16
  12. Mombaerts P. (2004) Genes and ligands for odorant, vomeronasal and taste receptors. Nature Reviews Neuroscience 5(4): 263-278
  13. Collaku A., Rankinen T. , Rice, T, et al.:  (2004) A genome-wide linkage scan for dietary energy and nutrient intakes: the Health, Risk Factors, Exercise Training, and Genetics (HERITAGE) Family Study. American Journal of Clinical Nutrition  79(5): 881-886
  14. Masson L.F., McNeill G. & Avenell A. (2003) Genetic variation and the lipid response to dietary intervention: a systematic review. American Journal of Clinical Nutrition 77(5): 1098-1111

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* Umami is a Japanese word meaning "savory" or "meaty" and specific to the detection of glutamates


Olfactory Receptor Database contains public and private sections which provide tools for investigators to analyse the functions of these very large gene families of G protein-coupled receptors. It also provides links to a local cluster of databases of related information in SenseLab, and to other relevant databases worldwide.

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