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The genes are not to blame

20.07.2018

Individualized dietary recommendations based on genetic information are currently a popular trend. A team at the Technical University of Munich (TUM) has systematically analyzed scientific articles and reached the following conclusion: There is no clear evidence for the effect of genetic factors on the consumption of total calories, carbohydrates, and fat. According to the current state of knowledge, the expedience of gene-based dietary recommendations has yet to be proven.

Overweight and obesity have become a global health problem. According to the World Health Organization, 39 percent of adults in EU countries have overweight. In Germany more than 50 percent of adults suffer from overweight, almost one fifth is according to the Robert Koch Institute currently considered obese. This is primarily due to the modern lifestyle which is characterized by low physical activity and high-calorie foods.


Also genetic factors play a role in the occurrence of obesity. To date, around a hundred genes (loci) have been identified which are related to the body mass index (BMI). However, the functioning of these genes as well as the biological mechanisms behind them are still largely unknown. The investigation of the relationship between genetic factors and nutrition can shed light on whether the genes which are linked to BMI play a role in nutrition.

Systematic literature search

... more about:
»BMI »MC4R »TUM »energy intake »genes »genetic factors

The initial database search of the TUM team revealed more than 10,000 scientific articles which were concerned with the topic. Of these, 39 articles were identified for a relationship between genetic factors and total energy, carbohydrate, or fat consumption. "In all studies, we most frequently encountered the fat mass and obesity (FTO) associated gene as well as the melanocortin 4 receptor gene (MC4R). There are indications of a relationship between these two genes and total energy intake," explains Christina Holzapfel, PhD, from the Institute of Nutritional Medicine at TUM.

However, the evaluation of the studies did not provide a uniform picture: "There is only limited evidence for the relationship between the FTO gene and low energy intake as well as between the MC4R gene and increased energy intake."

Hence, to date there exist no indications that certain genetic factors are associated with the total intake of calories, carbohydrates, and fat. The current state of knowledge is still too limited for deriving individual nutritional recommendations based on genetic information, e.g. for weight management, explains the researcher. Expert associations also agree with the latter statement.

"Human studies with detailed phenotyping, e.g. based on a genetic pre-analysis of the participants, are necessary in order to determine the interactions between genetic factors and diet on body weight. The "Personalized Nutrition & eHealth" Junior Research Group funded by the Federal Ministry of Education and Research, which is part of the enable nutrition cluster, is working precisely on this."

Wissenschaftliche Ansprechpartner:

Dr. rer. nat. Christina Holzapfel
Technical University of Munich
Nutritional Medicine
Phone: +49/89/289 249 23
Mail: christina.holzapfel@tum.de

Originalpublikation:

Theresa Drabsch, Jennifer Gatzemeier, Lisa Pfadenhauer, Hans Hauner, Christina Holzapfel: Associations between Single Nucleotide Polymorphisms and Total Energy, Carbohydrate, and Fat Intakes: A Systematic Review, Advances in Nutrition, Volume 9, Issue 4, 1 July 2018, Pages 425–453, https://doi.org/10.1093/advances/nmy024

Weitere Informationen:

http://www.enable-cluster.de/penut The interdisciplinary enable cluster is one of four nutrition research clusters funded by the Federal Ministry of Education and Research (BMBF) and based at the Weihenstephan Science Centre of the TUM in Freising. enable develops new strategies to feed people in different phases of life more healthily -from birth to old age.

Dr. Ulrich Marsch | Technische Universität München

Further reports about: BMI MC4R TUM energy intake genes genetic factors

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