Associations between Single Nucleotide Polymorphisms and Total Energy, Carbohydrate, and Fat Intakes: A Systematic Review. Issue 4 (19th July 2018)

• Record Type: Journal Article
• Authors: Drabsch, Theresa; Gatzemeier, Jennifer; Pfadenhauer, Lisa; Hauner, Hans; Holzapfel, Christina
• Is Part Of: Advances in nutrition. Volume 9:Issue 4(2018)
• Page Start: 425
• Page End: 453
• Publication Date: 2018-07-19
• Subjects: genetic variant -- single nucleotide polymorphism -- carbohydrate intake -- fat intake -- energy intake -- nutrigenomic; Nutrition -- Periodicals; Diet therapy -- Periodicals; Nutrition; Nutritional Physiological Phenomena; Nutritional Sciences; Periodicals; 613.205
• DOI: 10.1093/advances/nmy024
• Languages: English
• ISSNs: 2161-8313

Abstract

Abstract: A better understanding of the genetic underpinning of total energy, carbohydrate, and fat intake is a prerequisite to develop personalized dietary recommendations. For this purpose, we systematically reviewed associations between single nucleotide polymorphisms (SNPs) and total energy, carbohydrate, and fat intakes. Four databases were searched for studies that assessed an association between SNPs and total energy, carbohydrate, and fat intakes. Screening of articles and data extraction was performed independently by 2 reviewers. Articles in English or German language, published between 1994 and September 2017, on human studies in adults and without specific populations were considered for the review. In total, 39 articles, including 86 independent loci, met the inclusion criteria. The fat mass and obesity–associated ( FTO ) gene as well as the melanocortin 4 receptor ( MC4R ) locus were most frequently studied. Limited significant evidence of an association between the FTO SNP rs9939609 and lower total energy intake and between the MC4R SNP rs17782313 and higher total energy intake was reported. Most of the other identified loci showed inconsistent results. In conclusion, there is no consistent evidence that the investigated SNPs are associated with and predictive for total energy, carbohydrate, and fat intakes.