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Food Preference Patterns in a UK Twin Cohort
- Tess Pallister, Mastaneh Sharafi, Genevieve Lachance, Nicola Pirastu, Robert P. Mohney, Alex MacGregor, Edith J. M. Feskens, Valerie Duffy, Tim D. Spector, Cristina Menni
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- Journal:
- Twin Research and Human Genetics / Volume 18 / Issue 6 / December 2015
- Published online by Cambridge University Press:
- 28 September 2015, pp. 793-805
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- Article
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Food liking-disliking patterns may strongly influence food choices and health. Here we assess: (1) whether food preference patterns are genetic/environmentally driven; and (2) the relationship between metabolomics profiles and food preference patterns in a large population of twins. 2,107 individuals from TwinsUK completed an online food and lifestyle preference questionnaire. Principle components analysis was undertaken to identify patterns of food liking-disliking. Heritability estimates for each liking pattern were obtained by structural equation modeling. The correlation between blood metabolomics profiles (280 metabolites) and each food liking pattern was assessed in a subset of 1,491 individuals and replicated in an independent subset of monozygotic twin pairs discordant for the liking pattern (65 to 88 pairs). Results from both analyses were meta-analyzed. Four major food-liking patterns were identified (Fruit and Vegetable, Distinctive Tastes, Sweet and High Carbohydrate, and Meat) accounting for 26% of the total variance. All patterns were moderately heritable (Fruit and Vegetable, h2[95% CI]: 0.36 [0.28; 0.44]; Distinctive Tastes: 0.58 [0.52; 0.64]; Sweet and High Carbohydrate: 0.52 [0.45, 0.59] and Meat: 0.44 [0.35; 0.51]), indicating genetic factors influence food liking-disliking. Overall, we identified 14 significant metabolite associations (Bonferroni p < 4.5 × 10−5) with Distinctive Tastes (8 metabolites), Sweet and High Carbohydrate (3 metabolites), and Meat (3 metabolites). Food preferences follow patterns based on similar taste and nutrient characteristics and these groupings are strongly determined by genetics. Food preferences that are strongly genetically determined (h2 ≥ 0.40), such as for meat and distinctive-tasting foods, may influence intakes more substantially, as demonstrated by the metabolomic associations identified here.
24 - New Psychophysical Insights in Evaluating Genetic Variation in Taste
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- By Katharine Fast, Department of Surgery (Otolaryngology), Yale University School of Medicine, 333 Cedar Street, New Haven, CT 06520-8041, USA, Valerie B. Duffy, Department of Surgery (Otolaryngology), Yale University School of Medicine, 333 Cedar Street, New Haven, CT 06520-8041, USA, and School of Allied Health Sciences, University of Connecticut, Linda M. Bartoshuk, Department of Surgery (Otolaryngology), Yale University School of Medicine, 333 Cedar Street, New Haven, CT 06520-8041, USA
- Edited by Catherine Rouby, Université Lyon I, Benoist Schaal, Centre National de la Recherche Scientifique (CNRS), Paris, Danièle Dubois, Centre National de la Recherche Scientifique (CNRS), Paris, Rémi Gervais, Centre National de la Recherche Scientifique (CNRS), Paris, A. Holley, Centre National de la Recherche Scientifique (CNRS), Paris
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- Book:
- Olfaction, Taste, and Cognition
- Published online:
- 21 September 2009
- Print publication:
- 28 October 2002, pp 391-407
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Summary
How awful is “awful”? And is my “awful” the same as yours? The answers to these questions require comparing sensory or hedonic experiences across individuals, one of the most difficult tasks for psychophysicists. This chapter aims to trace the evolution of sensory scaling techniques intended to provide such comparisons, focusing on taste and using the discovery of taste blindness as a starting line. The past 70 years have been exciting times in psychophysics and have witnessed the development of methods useful for quantifying not only the oral impact of a stimulus but also its appeal.
For several generations, psychophysicists have been concerned about our ability to scale sensory experiences. A 1,000-Hz, 98-decibel blast is a 1,000-Hz, 98-decibel blast, but we recognize that it may sound far more intense to the department chair's grandson than to the department chair herself. We recognize this because we accept that a certain auditory deficit may accompany the blooming of wisdom, but how do we go about quantifying perceived sound intensity so that we can compare the experiences of the young and old directly? Our scale may start in silence, but if we have assimilated the idea that a given sound will be of different perceived intensities to different people, where do we anchor our scale besides the bottom? The perceived strength of a cleanser's odor works the same way: The same concentration of scent is added to each bottle at the factory, but the aroma may strike some as overpowering, while being barely detectable to others.