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Predicting fatty acid profiles in blood based on food intake and the FADS1 rs174546 SNP

Hallmann, J., Kolossa, S., Celis-Morales, C., Forster, H., O’Donovan, C. B., Woolhead, C., Macready, A. L., Fallaize, R., Marsaux, C. F. M., Tsirigoti, L., Efstathopoulou, E., Moschonis, G., Navas-Carretero, S., San-Cristobal, R., Godlewska, M., Surwiłło, A., Mathers, J. C., Gibney, E. R., Brennan, L., Walsh, M. C. , Lovegrove, J. A., Saris, W. H. M., Manios, Y., Martinez, J. A., Traczyk, I., Gibney, M. J. and Daniel, H. (2015) Predicting fatty acid profiles in blood based on food intake and the FADS1 rs174546 SNP. Molecular Nutrition & Food Research, 59 (12). pp. 2565-2573. ISSN 1613-4125

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To link to this item DOI: 10.1002/mnfr.201500414

Abstract/Summary

SCOPE: A high intake of n-3 PUFA provides health benefits via changes in the n-6/n-3 ratio in blood. In addition to such dietary PUFAs, variants in the fatty acid desaturase 1 (FADS1) gene are also associated with altered PUFA profiles. METHODS AND RESULTS: We used mathematical modelling to predict levels of PUFA in whole blood, based on MHT and bolasso selected food items, anthropometric and lifestyle factors, and the rs174546 genotypes in FADS1 from 1,607 participants (Food4Me Study). The models were developed using data from the first reported time point (training set) and their predictive power was evaluated using data from the last reported time point (test set). Amongst other food items, fish, pizza, chicken and cereals were identified as being associated with the PUFA profiles. Using these food items and the rs174546 genotypes as predictors, models explained 26% to 43% of the variability in PUFA concentrations in the training set and 22% to 33% in the test set. CONCLUSIONS: Selecting food items using MHT is a valuable contribution to determine predictors, as our models' predictive power is higher compared to analogue studies. As unique feature, we additionally confirmed our models' power based on a test set.

Item Type:Article
Refereed:Yes
Divisions:Interdisciplinary centres and themes > Food Chain and Health
Faculty of Life Sciences > School of Agriculture, Policy and Development > Economic and Social Sciences Division > Food Economics and Marketing (FEM)
Faculty of Life Sciences > School of Chemistry, Food and Pharmacy > Department of Food and Nutritional Sciences > Human Nutrition Research Group
Faculty of Life Sciences > School of Psychology and Clinical Language Sciences > Nutrition and Health
ID Code:42874
Uncontrolled Keywords:FADS1, fatty acids, n-6, n-3, linear regression model
Publisher:Wiley

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