A Genome-Wide Association Study in isolated populations reveals new genes associated to common food likings
- 823 Downloads
Food preferences are the first factor driving food choice and thus nutrition. They involve numerous different senses such as taste and olfaction as well as various other factors such as personal experiences and hedonistic aspects. Although it is clear that several of these have a genetic basis, up to now studies have focused mostly on the effects of polymorphisms of taste receptor genes. Therefore, we have carried out one of the first large scale (4611 individuals) GWAS on food likings assessed for 20 specific food likings belonging to 4 different categories (vegetables, fatty, dairy and bitter). A two-step meta-analysis using three different isolated populations from Italy for the discovery step and two populations from The Netherlands and Central Asia for replication, revealed 15 independent genome-wide significant loci (p < 5 × 10−8) for 12 different foods. None of the identified genes coded for either taste or olfactory receptors suggesting that genetics impacts in determining food likings in a much broader way than simple differences in taste perception. These results represent a further step in uncovering the genes that underlie liking of common foods that in the end will greatly help understanding the genetics of human nutrition in general.
KeywordsFood preferences Food consumption Food choice GWAS Association study Isolated populations
We would like to thank all the participants in the various studies for their contribution and support.
The SR study has been founded by the Region Friuli Venezia Giulia grant number 35\09 Linea 2 “Sulle tracce di Marco Polo: geni, gusto e loro implicazioni sulla salute lungo la Via della Seta”.
The INGI-FVG study was founded through the Italian Ministry of health.
We thank the inhabitants and the administrators of the Val Borbera for their participation in the study. A special thanks to Professor Clara Camaschella, Dr Silvia Bione, Dr Laura Crocco, Ms Maria Rosa Biglieri, Dr Diego Sabbi for help with the data collection. We thank Fondazione Compagnia di San Paolo, Torino, Fondazione Cariplo, Milano and Health Ministry (Progetto Finalizzato and Italian Centre for Disease Prevention and Control) for financial support.
The ERF study as a part of EUROSPAN (European Special Populations Research Network) was supported by European Commission FP6 STRP grant number 018947 (LSHG-CT-2006-01947) and also received funding from the European Community's Seventh Framework Programme (FP7/2007–2013)/grant agreement HEALTH-F4-2007-201413 by the European Commission under the programme “Quality of Life and Management of the Living Resources” of 5th Framework Programme (no. QLG2-CT-2002-01254). High-throughput analysis of the ERF data was supported by joint grant from Netherlands Organisation for Scientific Research and the Russian Foundation for Basic Research (NWO-RFBR 047.017.043). We are grateful to all study participants and their relatives, general practitioners and neurologists for their contributions and to P. Veraart for her help in genealogy, J. Vergeer for the supervision of the laboratory work and P. Snijders for his help in data collection. Statistical analyses were partly carried out on the Genetic Cluster Computer (http://www.geneticcluster.org) which is financially supported by the Netherlands Scientific Organization (NWO 480-05-003 PI: Posthuma) along with a supplement from the Dutch Brain Foundation and the VU University Amsterdam. This research was financially supported by BBMRI-NL, a Research Infrastructure financed by the Dutch Government (NWO 184.021.007). The work of LCK was partially funded by the FP7 projects MIMOmics (grant no. 305280) and Pain-Omics (grant no. 602736).
Conceived and designed the experiments: NP LN PG. Performed the experiments: NP SMW MT GP LCK AR PDA AD. Analyzed the data: NP MK CS. Contributed reagents/materials/analysis tools: CVD DT PG NA. Wrote the paper: NP MK LCK PG.
Compliance with ethical standards
Consent forms for clinical and genetic studies were signed by each participant and all research was conducted according to the ethical standards defined by the Helsinki declaration. The INGI-CARL, INGI-FVG and SR studies have been approved by the Institutional Review Board of IRCCS Burlo Garofolo PROT CE/v-78 in Trieste Italy. The INGI-VB study was approved by San Raffaele Hospital and Regione Piemonte ethical committees. The ERF study was approved by the Erasmus institutional medical-ethics committee in Rotterdam, The Netherlands
Conflict of interest
The authors declare no conflict of interest.
Competing financial interests
The author(s) declare no competing financial interests.
- 1.Diet, nutrition and the prevention of chronic diseases. World Health Organ. Tech. Rep. Ser. [Internet]. 2003 [cited 2014 Jun 2];916:i—viii, 1–149, backcover. Available from: http://www.ncbi.nlm.nih.gov/pubmed/12768890.
- 3.Tanaka T, Ngwa JS, van Rooij FJA, Zillikens MC, Wojczynski MK, Frazier-Wood AC. Genome-wide meta-analysis of observational studies shows common genetic variants associated with macronutrient intake. Am J Clin Nutr. 2013;97:1395–402. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3652928&tool=pmcentrez&rendertype=abstract.CrossRefPubMedPubMedCentralGoogle Scholar
- 4.Schatzkin A, Kipnis V, Carroll RJ, Midthune D, Subar AF, Bingham S. A comparison of a food frequency questionnaire with a 24-hour recall for use in an epidemiological cohort study: results from the biomarker-based Observing Protein and Energy Nutrition (OPEN) study. Int J Epidemiol. 2003;32:1054–62. Available from: http://www.ncbi.nlm.nih.gov/pubmed/14681273.CrossRefPubMedGoogle Scholar
- 5.International Food Information Council Foundation. The 2015 food & health survey: consumer attitudes toward food safety, nutrition & health. Washington, D.C.; 2015.Google Scholar
- 7.Pallister T, Sharafi M, Lachance G, Pirastu N, Mohney RP, MacGregor A, et al. Food preference patterns in a UK Twin Cohort. Twin Res Hum Genet. 2015.Google Scholar
- 10.Duffy VB, Hayes JE, Davidson AC, Kidd JR, Kidd KK, Bartoshuk LM. Vegetable intake in college-aged adults is explained by oral sensory phenotypes and TAS2R38 genotype. Chemosens Percept. 2010;3:137–48. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3000691&tool=pmcentrez&rendertype=abstract.CrossRefPubMedPubMedCentralGoogle Scholar
- 11.Hayes JE, Wallace MR, Knopik VS, Herbstman DM, Bartoshuk LM, Duffy VB. Allelic variation in TAS2R bitter receptor genes associates with variation in sensations from and ingestive behaviors toward common bitter beverages in adults. Chem Senses. 2011;36:311–9. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3038275&tool=pmcentrez&rendertype=abstract.CrossRefPubMedGoogle Scholar
- 12.Pirastu N, Robino A, Lanzara C, Athanasakis E, Esposito L, Tepper BJ, et al. Genetics of food preferences: a first view from silk road populations. J Food Sci. 2012. Available from: http://www.ncbi.nlm.nih.gov/pubmed/22888812.
- 13.Colares-Bento FCJ, Souza VC, Toledo JO, Moraes CF, Alho CS, Lima RM. Implication of the G145C polymorphism (rs713598) of the TAS2r38 gene on food consumption by Brazilian older women. Arch Gerontol Geriatr. 2016;54:e13–8. Available from: http://www.ncbi.nlm.nih.gov/pubmed/21763010.CrossRefGoogle Scholar
- 16.Sandell M, Hoppu U, Mikkilä V, Mononen N, Kähönen M, Männistö S. Genetic variation in the hTAS2R38 taste receptor and food consumption among Finnish adults. Genes Nutr. 2014;9:433. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=4235829&tool=pmcentrez&rendertype=abstract.CrossRefPubMedPubMedCentralGoogle Scholar
- 18.Jones LV, Peryam DR, Thurstone LL. development of a scale for measuring soldiers’food preferences b. J Food Sci. 1955;20:512–20. Available from: http://doi.wiley.com/10.1111/j.1365-2621.1955.tb16862.x.CrossRefGoogle Scholar
- 19.Coetzee H, Taylor JRN. The use and adaptation of the paired-comparison method in the sensory evaluation of hamburger-type patties by illiterate/semi-literate consumers. Food Qual Prefer. 1996;7:81–5. Available from: http://www.sciencedirect.com/science/article/pii/0950329395000399.CrossRefGoogle Scholar
- 22.J.G. D. Five point vs. eleven point scales: does it make a difference to data characteristics? Australas. J Mark Res. 2002;10:39–47.Google Scholar
- 26.Abecasis GR, Auton A, Brooks LD, DePristo MA, Durbin RM, Handsaker RE. An integrated map of genetic variation from 1,092 human genomes. Nature. 2012;491:56–65. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3498066&tool=pmcentrez&rendertype=abstract.CrossRefPubMedGoogle Scholar
- 28.Belonogova NM, Svishcheva GR, van Duijn CM, Aulchenko YS, Axenovich TI. Region-based association analysis of human quantitative traits in related individuals. PLoS One. 2013;8:e65395. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3684601&tool=pmcentrez&rendertype=abstract.CrossRefPubMedPubMedCentralGoogle Scholar
- 32.Spiegelberg BD, Xiong JP, Smith JJ, Gu RF, York JD. Cloning and characterization of a mammalian lithium-sensitive bisphosphate 3′-nucleotidase inhibited by inositol 1,4-bisphosphate. J Biol Chem. 1999;274:13619–28. Available from: http://www.ncbi.nlm.nih.gov/pubmed/10224133.CrossRefPubMedGoogle Scholar
- 34.Green E, Jacobson A, Haase L, Murphy C. Reduced nucleus accumbens and caudate nucleus activation to a pleasant taste is associated with obesity in older adults. Brain Res. 2011;1386:109–17. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3086067&tool=pmcentrez&rendertype=abstract.CrossRefPubMedPubMedCentralGoogle Scholar
- 35.Yang Q, Kathiresan S, Lin J-P, Tofler GH, O’Donnell CJ. Genome-wide association and linkage analyses of hemostatic factors and hematological phenotypes in the Framingham Heart Study. BMC Med Genet. 2007;8 Suppl 1:S12. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1995619&tool=pmcentrez&rendertype=abstract.CrossRefPubMedPubMedCentralGoogle Scholar
- 36.Kathiresan S, Manning AK, Demissie S, D’Agostino RB, Surti A, Guiducci C. A genome-wide association study for blood lipid phenotypes in the Framingham Heart Study. BMC Med Genet. 2007;8 Suppl 1:S17. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1995614&tool=pmcentrez&rendertype=abstract.CrossRefPubMedPubMedCentralGoogle Scholar
- 37.Nakabayashi K, Komaki G, Tajima A, Ando T, Ishikawa M, Nomoto J. Identification of novel candidate loci for anorexia nervosa at 1q41 and 11q22 in Japanese by a genome-wide association analysis with microsatellite markers. J Hum Genet. 2009;54:531–7. Available from: http://www.ncbi.nlm.nih.gov/pubmed/19680270.CrossRefPubMedGoogle Scholar
- 43.Ripke S, Sanders AR, Kendler KS, Levinson DF, Sklar P, Holmans PA, et al. R GP. Genome-wide association study identifies five new schizophrenia loci. Nat Genet. 2011;43:969–76. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3303194&tool=pmcentrez&rendertype=abstract.CrossRefGoogle Scholar
- 44.Nock NL, Wang X, Thompson CL, Song Y, Baechle D, Raska P. Defining genetic determinants of the Metabolic Syndrome in the Framingham Heart Study using association and structural equation modeling methods. BMC Proc. 2009;3 Suppl 7:S50. Available from: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2795950&tool=pmcentrez&rendertype=abstract.CrossRefPubMedPubMedCentralGoogle Scholar