Genotype-phenotype associations: modulation by diet and obesity

Obesity (Silver Spring). 2008 Dec;16 Suppl 3(Suppl 3):S40-6. doi: 10.1038/oby.2008.515.


Changes in diet are likely to reduce chronic disorders, but after decades of active research and heated discussion, the question still remains: what is the optimal diet to achieve this elusive goal? Is it a low-fat diet, as traditionally recommended by multiple medical societies? Or a high monounsaturated fat (MUFA) diet as predicated by the Mediterranean diet? Perhaps a high polyunsaturated fat (PUFA) diet based on the cholesterol-lowering effects? The right answer may be all of the above but not for everybody. A well-known phenomenon in nutrition research and practice is the dramatic variability in interindividual response to any type of dietary intervention. There are many other factors influencing response, and they include, among many others, age, sex, physical activity, alcohol, and smoking as well as genetic factors that will help to identify vulnerable populations/individuals that will benefit from a variety of more personalized and mechanistic-based dietary recommendations. This potential could and needs to be developed within the context of nutritional genomics that in conjunction with systems biology may provide the tools to achieve the holy grail of dietary prevention and therapy of chronic diseases and cancer. This approach will break with the traditional public health approach of "one size fits all." The current evidence based on nutrigenetics has begun to identify subgroups of individuals who benefit more from a low-fat diet, whereas others appear to benefit more from high MUFA or PUFA diets. The continuous progress in nutrigenomics will allow some time in the future to provide targeted gene-based dietary advice.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Body Mass Index
  • Diet*
  • Dietary Fats / pharmacology
  • Environment
  • Epigenesis, Genetic
  • Genetic Variation
  • Genotype
  • Humans
  • Metabolic Syndrome / genetics
  • Nutrigenomics*
  • Obesity / genetics*
  • Phenotype


  • Dietary Fats