A Scientific Perspective of Personalised Gene-Based Dietary Recommendations for Weight Management

Theresa Drabsch; Christina Holzapfel

doi:10.3390/nu11030617

journal article Open Access Mar 14, 2019

A Scientific Perspective of Personalised Gene-Based Dietary Recommendations for Weight Management

Theresa Drabsch

Christina Holzapfel

Nutrients Vol. 11 No. 3 pp. 617 · MDPI AG

View at Publisher Save 10.3390/nu11030617

Abstract

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.

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References

72

[1]

Lam "Analysis of energy metabolism in humans: A review of methodologies" Mol. Metab. (2016) 10.1016/j.molmet.2016.09.005

[2]

Crowley "Overview of human obesity and central mechanisms regulating energy homeostasis" Ann Clin. Biochem. (2008) 10.1258/acb.2007.007193

[3]

Congenital leptin deficiency is associated with severe early-onset obesity in humans

Carl T. Montague, I. Sadaf Farooqi, Jonathan P. Whitehead et al.

Nature 1997 10.1038/43185

[4]

Wiedmer "Ghrelin, obesity and diabetes" Nat. Clin. Pract. Endocrinol. Metab. (2007) 10.1038/ncpendmet0625

[5]

Woods "Central control of body weight and appetite" J. Clin. Endocrinol. Metab. (2008) 10.1210/jc.2008-1630

[6]

Mechanisms of CCK signaling from gut to brain

Helen E Raybould

Current Opinion in Pharmacology 2007 10.1016/j.coph.2007.09.006

[7]

Johnston "Comparison of weight loss among named diet programs in overweight and obese adults: A meta-analysis" JAMA (2014) 10.1001/jama.2014.10397

[8]

Sacks "Comparison of weight-loss diets with different compositions of fat, protein, and carbohydrates" N. Engl. J. Med. (2009) 10.1056/nejmoa0804748

[9]

Shai "Weight Loss with a Low-Carbohydrate, Mediterranean, or Low-Fat Diet" N. Engl. J. Med. (2008) 10.1056/nejmoa0708681

[10]

Gardner "Effect of Low-Fat vs Low-Carbohydrate Diet on 12-Month Weight Loss in Overweight Adults and the Association with Genotype Pattern or Insulin Secretion: The DIETFITS Randomized Clinical Trial" JAMA (2018) 10.1001/jama.2018.0245

[11]

Esposito "Mediterranean diet and weight loss: Meta-analysis of randomized controlled trials" Metab. Syndr. Relat. Disord. (2011) 10.1089/met.2010.0031

[12]

Jenkins "The effect of a plant-based low-carbohydrate (“Eco-Atkins”) diet on body weight and blood lipid concentrations in hyperlipidemic subjects" Arch. Intern. Med. (2009) 10.1001/archinternmed.2009.115

[13]

Jenkins "Effect of a 6-month vegan low-carbohydrate (‘Eco-Atkins’) diet on cardiovascular risk factors and body weight in hyperlipidaemic adults: A randomised controlled trial" BMJ Open (2014) 10.1136/bmjopen-2013-003505

[14]

Harris "Omega-6 fatty acids and risk for cardiovascular disease: A science advisory from the American Heart Association Nutrition Subcommittee of the Council on Nutrition, Physical Activity, and Metabolism; Council on Cardiovascular Nursing; and Council on Epidemiology and Prevention" Circulation (2009) 10.1161/circulationaha.108.191627

[15]

Bamberger, C., Rossmeier, A., Lechner, K., Wu, L., Waldmann, E., Stark, R.G., Altenhofer, J., Henze, K., and Parhofer, K.G. (2017). A Walnut-Enriched Diet Reduces Lipids in Healthy Caucasian Subjects, Independent of Recommended Macronutrient Replacement and Time Point of Consumption: A Prospective, Randomized, Controlled Trial. Nutrients, 9. 10.3390/nu9101097

[16]

Holzmann "Nutrition apps: Quality and limitations. An explorative investigation on the basis of selected apps" Ernaehrungs Umsch. (2017)

[17]

Krug "The dynamic range of the human metabolome revealed by challenges" FASEB J. Off. Publ. Fed. Am. Soc. Exp. Biol. (2012)

[18]

Personalized Nutrition by Prediction of Glycemic Responses

David Zeevi, Tal Korem, Niv Zmora et al.

Cell 2015 10.1016/j.cell.2015.11.001

[19]

Korem "Bread Affects Clinical Parameters and Induces Gut Microbiome-Associated Personal Glycemic Responses" Cell Metab. (2017) 10.1016/j.cmet.2017.05.002

[20]

Wopereis "Multi-parameter comparison of a standardized mixed meal tolerance test in healthy and type 2 diabetic subjects: The PhenFlex challenge" Genes Nutr. (2017) 10.1186/s12263-017-0570-6

[21]

De Toro-Martin, J., Arsenault, B.J., Despres, J.P., and Vohl, M.C. (2017). Precision Nutrition: A Review of Personalized Nutritional Approaches for the Prevention and Management of Metabolic Syndrome. Nutrients, 9. 10.3390/nu9080913

[22]

Nizel "Personalized nutrition counseling" ASDC J. Dent. Child. (1972)

[23]

Brug "The application and impact of computer-generated personalized nutrition education: A review of the literature" Patient Educ. Couns. (1999) 10.1016/s0738-3991(98)00131-1

[24]

Kuznesof "Factors influencing European consumer uptake of personalised nutrition. Results of a qualitative analysis" Appetite (2013) 10.1016/j.appet.2013.03.001

[25]

Wang "Precision nutrition for prevention and management of type 2 diabetes" Lancet. Diabetes Endocrinol. (2018) 10.1016/s2213-8587(18)30037-8

[26]

Anthony "Systems biology of personalized nutrition" Nutr. Rev. (2017) 10.1093/nutrit/nux029

[27]

Daniel "Personalisierte Ernährung" J. Für Ernährungsmedizin (2016)

[28]

Nielsen, D.E., and El-Sohemy, A. (2014). Disclosure of genetic information and change in dietary intake: A randomized controlled trial. PLoS ONE, 9. 10.1371/journal.pone.0112665

[29]

Poinhos, R., van der Lans, I.A., Rankin, A., Fischer, A.R., Bunting, B., Kuznesof, S., Stewart-Knox, B., and Frewer, L.J. (2014). Psychological determinants of consumer acceptance of personalised nutrition in 9 European countries. PLoS ONE, 9. 10.1371/journal.pone.0110614

[30]

The Health Belief Model: A Decade Later

Nancy K. Janz, Marshall H. Becker

Health Education Quarterly 1984 10.1177/109019818401100101

[31]

Anderson "How to implement dietary changes to prevent the development of metabolic syndrome" Br. J. Nutr. (2000) 10.1017/s0007114500001112

[32]

Bouchard "Genetic influences on the response of body fat and fat distribution to positive and negative energy balances in human identical twins" J. Nutr. (1997) 10.1093/jn/127.5.943s

[33]

Stunkard "An adoption study of human obesity" N. Engl. J. Med. (1986) 10.1056/nejm198601233140401

[34]

Levy "The polymorphism at codon 54 of the FABP2 gene increases fat absorption in human intestinal explants" J. Biol. Chem. (2001) 10.1074/jbc.m105713200

[35]

Hegele "Genetic variation of intestinal fatty acid-binding protein associated with variation in body mass in aboriginal Canadians" J. Clin. Endocrinol. Metab. (1996)

[36]

Tontonoz "mPPAR gamma 2: Tissue-specific regulator of an adipocyte enhancer" Genes Dev. (1994) 10.1101/gad.8.10.1224

[37]

Stimulation of adipogenesis in fibroblasts by PPARγ2, a lipid-activated transcription factor

Peter Tontonoz, Erding Hu, Bruce M. Spiegelman

Cell 1994 10.1016/0092-8674(94)90006-x

[38]

Deeb "A Pro12Ala substitution in PPARgamma2 associated with decreased receptor activity, lower body mass index and improved insulin sensitivity" Nat. Genet. (1998) 10.1038/3099

[39]

Hagg "Gene-based meta-analysis of genome-wide association studies implicates new loci involved in obesity" Hum. Mol. Genet. (2015) 10.1093/hmg/ddv379

[40]

Locke "Genetic studies of body mass index yield new insights for obesity biology" Nature (2015) 10.1038/nature14177

[41]

Thorleifsson "Genome-wide association yields new sequence variants at seven loci that associate with measures of obesity" Nat. Genet. (2009) 10.1038/ng.274

[42]

Speliotes "Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index" Nat. Genet. (2010) 10.1038/ng.686

[43]

Loos "The genetics of adiposity" Curr. Opin. Genet. Dev. (2018) 10.1016/j.gde.2018.02.009

[44]

A Common Variant in the FTO Gene Is Associated with Body Mass Index and Predisposes to Childhood and Adult Obesity

Timothy M. Frayling, Nicholas J. Timpson, Michael N. Weedon et al.

Science 2007 10.1126/science.1141634

[45]

Dina "Variation in FTO contributes to childhood obesity and severe adult obesity" Nat. Genet. (2007) 10.1038/ng2048

[46]

Scuteri, A., Sanna, S., Chen, W.M., Uda, M., Albai, G., Strait, J., Najjar, S., Nagaraja, R., Orru, M., and Usala, G. (2007). Genome-wide association scan shows genetic variants in the FTO gene are associated with obesity-related traits. PLoS Genet., 3. 10.1371/journal.pgen.0030115

[47]

Claussnitzer "FTO Obesity Variant Circuitry and Adipocyte Browning in Humans" N. Engl. J. Med. (2015) 10.1056/nejmoa1502214

[48]

Larder "Obesity-associated gene TMEM18 has a role in the central control of appetite and body weight regulation" Proc. Natl. Acad. Sci. USA (2017) 10.1073/pnas.1707310114

[49]

Wiemerslage "The Drosophila ortholog of TMEM18 regulates insulin and glucagon-like signaling" J. Endocrinol. (2016) 10.1530/joe-16-0040

[50]

Cone "Anatomy and regulation of the central melanocortin system" Nat. Neurosci. (2005) 10.1038/nn1455

Showing 50 of 72 references

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Details

Published: Mar 14, 2019
Vol/Issue: 11(3)
Pages: 617
License: View

Authors

T

Theresa Drabsch

Institute for Nutritional Medicine, University Hospital Klinikum rechts der Isar, Technical University of Munich, Georg-Brauchle-Ring 62, 80992 Munich, Germany

C

Christina Holzapfel

Institute for Nutritional Medicine, University Hospital Klinikum rechts der Isar, Technical University of Munich, Georg-Brauchle-Ring 62, 80992 Munich, Germany

Funding

Bundesministerium für Bildung und Forschung Award: 01EA1709

Cite This Article

Theresa Drabsch, Christina Holzapfel (2019). A Scientific Perspective of Personalised Gene-Based Dietary Recommendations for Weight Management. Nutrients, 11(3), 617. https://doi.org/10.3390/nu11030617

A Scientific Perspective of Personalised Gene-Based Dietary Recommendations for Weight Management

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