Cargando…
A Scientific Perspective of Personalised Gene-Based Dietary Recommendations for Weight Management
Various studies showed that a “one size fits all” dietary recommendation for weight management is questionable. For this reason, the focus increasingly falls on personalised nutrition. Although there is no precise and uniform definition of personalised nutrition, the inclusion of genetic variants fo...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6471589/ https://www.ncbi.nlm.nih.gov/pubmed/30875721 http://dx.doi.org/10.3390/nu11030617 |
_version_ | 1783412062246928384 |
---|---|
author | Drabsch, Theresa Holzapfel, Christina |
author_facet | Drabsch, Theresa Holzapfel, Christina |
author_sort | Drabsch, Theresa |
collection | PubMed |
description | Various studies showed that a “one size fits all” dietary recommendation for weight management is questionable. For this reason, the focus increasingly falls on personalised nutrition. Although there is no precise and uniform definition of personalised nutrition, the inclusion of genetic variants for personalised dietary recommendations is more and more favoured, whereas scientific evidence for gene-based dietary recommendations is rather limited. The purpose of this article is to provide a science-based viewpoint on gene-based personalised nutrition and weight management. Most of the studies showed no clinical evidence for gene-based personalised nutrition. The Food4Me study, e.g., investigated four different groups of personalised dietary recommendations based on dietary guidelines, and physiological, clinical, or genetic parameters, and resulted in no difference in weight loss between the levels of personalisation. Furthermore, genetic direct-to-consumer (DTC) tests are widely spread by companies. Scientific organisations clearly point out that, to date, genetic DTC tests are without scientific evidence. To date, gene-based personalised nutrition is not yet applicable for the treatment of obesity. Nevertheless, personalised dietary recommendations on the genetic landscape of a person are an innovative and promising approach for the prevention and treatment of obesity. In the future, human intervention studies are necessary to prove the clinical evidence of gene-based dietary recommendations. |
format | Online Article Text |
id | pubmed-6471589 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-64715892019-04-25 A Scientific Perspective of Personalised Gene-Based Dietary Recommendations for Weight Management Drabsch, Theresa Holzapfel, Christina Nutrients Review Various studies showed that a “one size fits all” dietary recommendation for weight management is questionable. For this reason, the focus increasingly falls on personalised nutrition. Although there is no precise and uniform definition of personalised nutrition, the inclusion of genetic variants for personalised dietary recommendations is more and more favoured, whereas scientific evidence for gene-based dietary recommendations is rather limited. The purpose of this article is to provide a science-based viewpoint on gene-based personalised nutrition and weight management. Most of the studies showed no clinical evidence for gene-based personalised nutrition. The Food4Me study, e.g., investigated four different groups of personalised dietary recommendations based on dietary guidelines, and physiological, clinical, or genetic parameters, and resulted in no difference in weight loss between the levels of personalisation. Furthermore, genetic direct-to-consumer (DTC) tests are widely spread by companies. Scientific organisations clearly point out that, to date, genetic DTC tests are without scientific evidence. To date, gene-based personalised nutrition is not yet applicable for the treatment of obesity. Nevertheless, personalised dietary recommendations on the genetic landscape of a person are an innovative and promising approach for the prevention and treatment of obesity. In the future, human intervention studies are necessary to prove the clinical evidence of gene-based dietary recommendations. MDPI 2019-03-14 /pmc/articles/PMC6471589/ /pubmed/30875721 http://dx.doi.org/10.3390/nu11030617 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Drabsch, Theresa Holzapfel, Christina A Scientific Perspective of Personalised Gene-Based Dietary Recommendations for Weight Management |
title | A Scientific Perspective of Personalised Gene-Based Dietary Recommendations for Weight Management |
title_full | A Scientific Perspective of Personalised Gene-Based Dietary Recommendations for Weight Management |
title_fullStr | A Scientific Perspective of Personalised Gene-Based Dietary Recommendations for Weight Management |
title_full_unstemmed | A Scientific Perspective of Personalised Gene-Based Dietary Recommendations for Weight Management |
title_short | A Scientific Perspective of Personalised Gene-Based Dietary Recommendations for Weight Management |
title_sort | scientific perspective of personalised gene-based dietary recommendations for weight management |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6471589/ https://www.ncbi.nlm.nih.gov/pubmed/30875721 http://dx.doi.org/10.3390/nu11030617 |
work_keys_str_mv | AT drabschtheresa ascientificperspectiveofpersonalisedgenebaseddietaryrecommendationsforweightmanagement AT holzapfelchristina ascientificperspectiveofpersonalisedgenebaseddietaryrecommendationsforweightmanagement AT drabschtheresa scientificperspectiveofpersonalisedgenebaseddietaryrecommendationsforweightmanagement AT holzapfelchristina scientificperspectiveofpersonalisedgenebaseddietaryrecommendationsforweightmanagement |